Jobs ML / AI

Senior AI Engineer / AI Product Architect

Location: Remote
Industry: AI for Engineering, BIM, MEP Design, Industrial Facilities, Life Science

About the Role

We are looking for a Senior AI Engineer / AI Product Architect who has already been involved in building and launching a real AI-based product — not just prototypes, demos, or internal experiments.

This person should have hands-on experience in developing AI systems that solve complex, high-value business or engineering problems and are already used by paying customers or real enterprise users.

For MEPAIA, we are not looking for someone who only knows how to connect an LLM API to a chatbot. We need someone who understands how to build AI-powered workflows, where AI is integrated into a real software product, interacts with complex data, supports decision-making, and automates meaningful parts of professional work.

The ideal candidate has worked on a challenging AI product comparable in complexity to products such as Consigli, Augmenta, Endra AI, or other AI-native engineering, construction, design, automation, robotics, industrial, or enterprise software platforms.

What We Need

We need someone who can help us move from a successful proof-of-concept and early product vision toward a scalable AI product architecture.

The role combines:

• AI system design
• LLM / agentic workflow architecture
• productization of AI features
• integration with complex engineering software and data structures
• evaluation, reliability, and performance of AI outputs
• collaboration with domain experts in MEP, BIM, Revit, and industrial design

This is a senior role for someone who has already seen what it takes to turn AI from “interesting demo” into a product that customers actually use.

Key Responsibilities

• Design and lead the AI architecture for MEPAIA’s next product stages.

• Build AI workflows that translate engineering intent into executable software

  actions.

• Develop AI agents / copilots that can interact with structured engineering data, BIM models, documentation, calculations, and design rules.
• Work with Revit/BIM automation teams to connect AI reasoning with real design execution.
• Define how LLMs, classical algorithms, rule-based engineering logic, retrieval systems, and software automation should work together.
• Build robust evaluation methods for AI-generated outputs.
• Improve reliability, explainability, and repeatability of AI workflows.
• Help define the technical roadmap from MVP toward a future AI Engineer for MEP design.
• Work closely with founders, software engineers, and domain experts to convert MEP engineering knowledge into scalable AI functionality.

• Support technical discussions with investors, strategic partners, and early enterprise customers when needed.

   

  Required Experience

• Proven experience in building an AI-based product that reached real users, customers, or commercial deployment.
• Strong hands-on experience with LLMs, AI agents, RAG systems, tool use, function calling, or similar AI architectures.
• Experience designing AI workflows beyond simple chatbots.
• Strong software engineering background.
• Experience with production-grade systems, not only research notebooks or demos.
• Ability to work with complex domain-specific data and workflows.
• Understanding of how to evaluate AI outputs and reduce hallucinations or unreliable behavior.
• Ability to bridge product, engineering, and business requirements.

• Experience working in a startup, scaleup, or high-velocity product environment.

   

  Strong Plus

  Experience in one or more of the following areas would be highly valuable:

• AEC tech / ConTech / BIM software
• Revit, Autodesk ecosystem, IFC, CAD/BIM data structures
• Spatial AI / 3D reasoning / geometry-aware AI
• Engineering automation
• Robotics, industrial automation, or simulation
• AI for construction, infrastructure, manufacturing, or data centers
• Multi-agent systems
• AI copilots for professional software
• Enterprise SaaS

• Products similar in complexity to Consigli, Augmenta, Endra AI, TestFit, Finch, Hypar, or other AI-driven design platforms

   

  What This Role Is Not
  This is not a role for someone whose main experience is:

• building generic chatbots
• writing prompts only
• experimenting with ChatGPT wrappers
• doing academic ML without product deployment
• creating AI demos that never reached real users

• working only on marketing automation or simple customer-support bots

  We are looking for someone who has helped build serious AI software for serious workflows.

We are looking for a highly experienced Senior Sitecore (Sitecore AI) Developer to join a large-scale, long-term project. This role requires a top-level professional with deep expertise in Sitecore and strong communication skills.

Key Requirements
5+ years of commercial experience in software development
Proven experience with Sitecore (Sitecore AI)
Valid Sitecore certification (including Sitecore AI) is MANDATORY 
Strong hands-on experience building websites using Sitecore
English level: Upper-Intermediate or higher (proactive communication)
Ability to work independently and take ownership
 

Responsibilities
Develop and maintain websites using Sitecore (Sitecore AI)
Collaborate with stakeholders and participate in technical discussions
Ensure high-quality, scalable, and maintainable solutions

Project Details
Type: Long-term project (6+ months)
Engagement: Full-time
Cooperation type: Freelance

Interview Process
Internal HR interview
Internal technical interview
Final interview

#WeAreIn for jobs that impact everyone's life. What if your ideas could change the way the world connects, powers up, or thinks? As a Senior AI/ML Engineer on our Research & Development team, you'll have the opportunity to merge creativity with your technical expertise by shaping the future of technology, driving groundbreaking projects, and bringing new ideas to life. Are you in?

Key responsibilities in your new role

Work on innovative IoT, Industrial, and Automotive technologies in a fast-moving R&D team, turning ideas into real products and patents. 

• Design and develop efficient Neural Network (NN) models with sophisticated architectures for embedded domain, strongly involving application-specific knowledge
• Plan and execute practical experiments to collect/create high-quality datasets
• Combine NN and classic signal processing approaches to make the highly efficient pipelines of problem solving
• Implement the developed solutions under real-world end-user scenarios and requirements and verify its functionality at the Infineon hardware (PSOC, wireless SOCs)
• Help with ML/AI related design and implementation in different team projects

Your Profile

Qualifications and skills to help you succeed

• A master’s degree in electrical engineering or computer science (or equivalent) and 2-3 years of related research/engineering experience
• Strong background in mathematical modeling and numerical analysis
• Knowledge of modern NN architectures, Machine Learning tools and trends
• Proficiency in Python and at least one ML framework (PyTorch or TensorFlow)
• Experience with at least one of the following: signal / speech /image / video processing / wireless communication is a plus
• Understanding of embedded systems and Knowledge of Nvidia Deep Learning framework, and familiarity with patents, papers, publications on relevant technical subject matter is a plus
• Intermediate English writing, communication, and presentation skills

Please send us your CV in English.

We're partnered with an AI company that cleans up and enriches messy product data (PDFs, spreadsheets, images, CAD files) turning it into clean, marketplace-ready catalogs for brands and retailers selling on Shopify, Amazon, Walmart, and large PIM/ERP systems. We're helping the company bring on a few more engineers – one of the positions is this Data Scientist one.

Stack: Python / FastAPI on the backend, React / Next.js on the frontend, LLMs throughout. 

Engagement: Full-time, fully remote.

=====

You'll own the ML that powers the enrichment, classification, and validation pipelines — the core of the product. Real data, large scale, noisy inputs, a lot of LLM work alongside classical ML.

What you'll do

• Build classification, extraction, and enrichment models over product data (text, images, metadata)
• Design and ship LLM pipelines – RAG, extraction, validation – in production, not just notebooks
• Run experiments and build evaluation frameworks you actually trust
• Work with engineering to deploy models, not hand them off

We're looking for

• 4-7+ years in data science / ML
• Strong Python (pandas, sklearn, PyTorch, TensorFlow, etc)
• Real experience with LLMs, NLP, CV
• Solid instincts on model evaluation and data quality
• You've worked on messy real-world data and know how to handle it
• You're comfortable working with a significant overlap with the US Pacific Time
• Your conversational English is strong (you will be speaking with your teammates daily)

Nice to have

• Product / catalog / e-commerce data experience
• Experience with vector DBs, embeddings, RAG in production

We seek a Strong Middle ML / AI Engineer to join our team on a humanitarian transparency platform. This is a hands-on engineering role focused on building machine learning models and data pipelines — primarily around deduplication, anomaly detection, and statistical analysis of humanitarian data.

 

🧙‍♂️ In This Role You Will

• Design, build, and maintain ML models for deduplication, anomaly detection, and predictive analytics.
• Work with structured humanitarian data — beneficiary records, financial transactions, procurement flows.
• Build and maintain data processing pipelines using Python (Pandas, NumPy, scikit-learn).
• Collaborate with the backend team to expose ML/AI outputs via APIs.
• Monitor model performance and iterate based on real-world feedback.
• Document your work and support knowledge sharing within the team.
  
  
   

🎯 You May Be Interested If

• You enjoy working with messy, real-world data and turning it into reliable ML outputs.
• You care about model quality, reproducibility, and practical impact.
• You're comfortable applying classical ML approaches to solve concrete business problems.
• You're excited to collaborate in a remote, cross-functional environment.
• You value autonomy, clear communication, and working in a supportive, small-team setting.
  
   

👌 Role Requirements

• 3+ years of experience in ML engineering, data science, or a closely related role.
• Strong Python skills: Pandas, NumPy, scikit-learn.
• Experience building and deploying ML models in production environments.
• Solid understanding of data pipeline design and data quality practices.
• Familiarity with cloud platforms (Azure or AWS) for ML workloads.
• Proficiency with Git and standard development tooling.
• English proficiency at B1 level or higher.
   

Nice to have:

• Experience with PyTorch or TensorFlow.
• Hands-on experience with LLM integrations (OpenAI, Anthropic, or similar).
• Familiarity with ML experiment tracking tools (e.g. MLflow, Weights & Biases).
• Experience with GIS or geospatial data.
• Background in fraud detection, entity resolution, or deduplication tasks.
• Familiarity with Docker and CI/CD workflows for ML pipelines.
  
   

💻 Working Conditions

• Employment Type: Full-Time
• This is a fully remote position with the entire team across Ukraine.
• 20 working days of paid vacation per year.
• The team collaboratively defines deadlines, ensuring a balanced and manageable workload. The focus is on delivering commitments on time.
• Flexible working hours to promote a healthy work-life balance.

About Us

TytoNyx is building an agile AI-powered QMS platform for medical device manufacturers. Our system audits document portfolios against FDA guidance, ISO/IEC standards, cybersecurity expectations, and internal QMS requirements. We already have a functional MVP. We are now hardening the AI layer and backend for reliability, scalability, and production use.

Role Summary

We’re hiring a Senior Software Engineer with strong production GenAI experience to improve the AI core of our regulatory document audit platform. The main focus is AI reliability: RAG, document understanding, evidence extraction, citation grounding, structured outputs, evaluation, and repeatable audit workflows. We need someone who can build production AI systems with solid software engineering practices, clean backend architecture, testing, observability, and AWS deployment.

Responsibilities

• Production GenAI Systems Improve existing AI workflows for regulatory document audits, gap analysis, evidence extraction, compliance reasoning, and report generation. Strengthen RAG pipelines, Improve citation grounding so audit findings link back to source documents, requirements, and supporting evidence. Build AI evaluation and regression testing pipelines for accuracy, completeness, consistency, and failure modes. Work directly with AWS Bedrock, Anthropic Claude, and OpenAI APIs in production.
   
• Regulatory Document Intelligence Improve processing of PDFs, Word documents, spreadsheets, QMS records, cybersecurity files, risk files, design-control documents, and submission artifacts. Build workflows for document classification, metadata extraction, clause mapping, evidence detection, requirement matching, and gap identification.

• Backend & Reliability Harden the existing MVP for production use. Improve API design, data models, background jobs, file-processing workflows, and long-running AI job orchestration. Add retries, timeouts, error handling, job status tracking, logging, and recovery paths. Improve scalability for larger document portfolios and multiple customer audit runs. Write clean, testable, maintainable code with strong code review and CI/CD practices.

• AWS & Production Infrastructure Support AWS-based deployment for AI and backend services. Work with ECS/Fargate or Lambda, RDS/PostgreSQL, S3, SQS, Step Functions, OpenSearch or vector databases, Secrets Manager, KMS, CloudWatch, IAM, and AWS Bedrock. Improve monitoring, alerting, environment separation, secure configuration, and operational documentation.

Required Qualifications

• 5+ years of professional software engineering experience. 2+ years building production GenAI, LLM, RAG, document intelligence, or AI workflow systems.

• Strong Python experience. Experience with FastAPI, Django, Flask, or similar backend frameworks. Strong experience with embeddings, retrieval, structured outputs, prompt orchestration, evaluation, and source-grounded generation. Experience with vector search, semantic search, or document retrieval systems.

• AWS production experience. Solid backend fundamentals: APIs, PostgreSQL, queues, workers, Lambda, object storage, background jobs, and file-processing pipelines. Strong software engineering habits: testing, CI/CD, code review, logging, monitoring, documentation, and maintainable architecture.

About TytoNyx Inc.

TytoNyx is a young, dynamic startup poised to disrupt the medical device manufacturing sector with an amazing idea whose sky's-the-limit potential is limitless. Our innovative spirit fuels our cloud-based platform, which leverages advanced AI to streamline and improve quality management processes. We’re dedicated to positively transforming healthcare outcomes as a team of enthusiastic pioneers.

Atlas Technica’s mission is to shoulder IT management, user support, and cybersecurity for our clients, who are hedge funds and other investment firms. Founded in 2016, we have grown 100% year over year through our uncompromising focus on service.

We value ownership, execution, growth, intelligence, and camaraderie. We are looking for people who share our Core Values, thrive, and contribute to this environment while putting the customer first. At Atlas Technica, we offer a competitive salary, comprehensive benefits, and great perks to our global Team. We strive to maintain a professional yet friendly environment while promoting professional and career development for our Team Members. Join Atlas Technica now!

Design and deploy intelligent chatbots using Foundry Workflows, Microsoft Agent Framework, OpenAI. Build and operate multi-agent orchestration pipelines with Azure AI Foundry and Model Context Protocol (MCP). Integrate AI with enterprise systems via RESTful APIs, ensuring compliance with security and privacy standards. Stay current with LLM advancements, collaborate across teams, and mentor junior engineers.

Responsibilities:

AI Agent & Chatbot Development

• Design, build, and deploy intelligent conversational agents using Foundry Workflows, Microsoft Agent Framework, OpenAI.
• Develop prompt strategies and manage datasets to support context-aware, multi-turn dialogue and accurate responses.
• Conduct rapid prototyping to validate technical feasibility and demonstrate business value of AI-driven solutions.
• Design agentic loops with task decomposition, state passing between agents, and workflow enforcement for multi-step ticket resolution.

• Implement structured error responses and graceful degradation in agent tool calls, including timeout handling, retry logic, and fallback cascades.

   

Data & Model Engineering

• Build and maintain data ingestion and indexing pipelines for Azure AI Search and Cosmos DB.

• Evaluate and optimize AI system performance for accuracy, scalability, latency, and cost-efficiency.

   

System Integration & Architecture

• Architect and implement integration between AI and enterprise systems (e.g., ConnectWise PSA, Confluence, etc.) using RESTful APIs.
• Implement and maintain MCP servers (Model Context Protocol) for secure, typed tool integration between AI agents and enterprise APIs.
• Deploy containerized services to Azure using multi-stage builds and Azure Pipelines CI/CD.
• Security, Compliance & Governance
• Ensure AI systems comply with data privacy regulations (e.g., GDPR) and enterprise-grade security standards.

• Implement access controls, data encryption, and audit logging for sensitive AI workflows.

   

Research & Innovation

• Stay current with evolving LLM technologies, frameworks and methodologies.

• Evaluate emerging tools and techniques to continuously improve solution quality and delivery speed.

   

Collaboration & Leadership

• Work closely with cross-functional teams to interpret business requirements and recommend LLM-driven solutions.
• Contribute to technical and architectural decisions, ensuring alignment with strategic goals.

• Mentor junior engineers and support knowledge sharing across the team.

   

Operational Excellence

• Take ownership of incident resolution, and bug fixes.
• Create and maintain technical documentation for AI systems, models, and integration workflows.

Requirements:

• English level — B2 or higher
• 5+ years of experience in AI engineering and .NET software development (.NET 10, ASP.NET Core/WebAPI, C#) with frontend experience in React 19 / Next.js 15 / TypeScript, with a focus on Azure-based solutions.
• Experience building intelligent chatbots and autonomous agents (Agentic AI) that perform real actions, plan, reason, and act with minimal human input; familiar with multi-agent orchestration and agent memory.
• Strong expertise in embeddings, search, and prompt engineering.
• Strong understanding of large language models (LLMs), their limitations, and modern capabilities (e.g., GPT, Claude, Gemini).
• Hands-on experience with Azure AI services (Azure AI Foundry, Azure OpenAI, Azure AI Search) and hands-on experience with MCP or similar protocols for secure, scalable integration between AI agents and enterprise systems.
• Familiarity with multi-agent orchestration patterns: coordinator-subagent workflows, maker-checker validation, signal-based confidence scoring, and context preservation across multi-turn interactions.
• Experience designing prompts with explicit evaluation criteria, few-shot techniques, structured output via JSON schemas, and validation/retry loops for reliable LLM responses.
• Awareness of AI-specific security concerns: PII handling, data boundary enforcement, prompt injection prevention, and compliance considerations (e.g., GDPR).

• Ability to write clean, maintainable, and testable code following SOLID principles and Clean Architecture patterns.

   

Desirable Qualities:

• Understanding of AI solution architecture patterns: LLM gateway/service layer, retrieval layer, orchestration/agent layer, and evaluation/observability layer.
• Experience testing AI-enabled components using deterministic seams (mocked LLM clients, retrievers, tools), scenario-based tests, and regression/evaluation datasets for non-deterministic outputs.
• Understanding of retrieval systems (keyword search, vector search, embeddings) and ranking algorithms
• Familiarity with AI/ML versioning practices: prompt version control with semantic tagging, evaluation baseline tracking, dataset versioning, experiment reproducibility.
• Familiarity with deploying, monitoring, and maintaining ML models in production environments.
• Experience with Azure Cosmos DB, Azure Container Apps, Docker containerization
• Familiarity with CI/CD pipelines and DevOps practices.
• AI-102
• Experience with Application Insights telemetry, distributed tracing.
• Prior experience integrating AI agents with enterprise platforms like ConnectWise PSA, Confluence, SPO, etc.

Atlas Technica is proud to be an Equal Employment Opportunity employer. We do not discriminate based upon race, religion, color, national origin, gender, sexual orientation, gender identity, age, status as a protected veteran, status as an individual with a disability, or other applicable legally protected characteristics.

About

We are building an AI-native SaaS for real estate. The product is a PropTech SaaS platform where LLMs and AI agents are not bolted on top - they are the architecture. Owners, operators and guests interact with the AI system through natural language. AI autonomously generates compliance documents, routes staff, answers guest queries from RAG-indexed knowledge base in real time and orchestrates financial split-payments.

But the product is only half of it.

We are equally an AI-first engineering organization. The way we build is as differentiated as what we build. Our daily development loop - specification, implementation, code review, testing, deployment, on-call response - should run on a custom orchestrator of coding and operations agents. Human engineers operate at the level of intent, architecture, judgment and review. Agents should do most of the typing.

The role

This is the role that defines how that system works and how we build the product.

This is a hands-on technical leadership role at the core of the company's future, with a single defining characteristic: you will architect both the product development & testing approach and the AI based engineering system that builds it.

You will own the design, construction and operation of an internal AI-first development platform - the orchestrator, the agent fleet, the specification format, the evaluation harness, the CI/CD wiring - that lets a small team of senior humans ship at the velocity and surface area of a larger conventional team. You will decide what the human engineering team does, what agents do.

You will simultaneously own the production AI layer of the product itself - RAG pipelines, agent workflows, prompt strategy, vector memory - because the same intuition that makes the engineering org work makes the product work.

You will write production code daily. You will read agent diffs daily. You will build and tune evals continuously. 

We operate in a fast-moving startup environment where speed and precision both matter. You must be opinionated about which engineering tasks AI does well today, which it does not and how to close that gap inside our codebase deliberately.

What you will own & do

AI-First Engineering System (the differentiator)

• Build and operate the AI-first engineering system: design the orchestrator (task decomposition, agent coordination, review gates, deployment/rollback) and manage a fleet of coding, review, testing, and ops agents.
• Establish a spec-driven development model: convert product intent into machine-readable specs that agents can implement, test, and evolve reliably over time.
• Define governance and trust: set clear boundaries for agent autonomy vs. human approval, implement verification layers (evals, tests, canaries, traces), and codify standards as machine-readable rules.
• Continuously optimize performance and autonomy: run evaluation frameworks (A/B tests, drift detection, cost/latency tracking), make model/infra decisions, and increase the share of SDLC handled autonomously each quarter.

Technical Architecture & Strategy

• Define and own the full technical architecture of the SaaS platform: service boundaries, API design, data models and infrastructure
• Make fast, reasoned architectural trade-offs under startup timelines without accumulating critical technical debt
• Set the technical direction for AI integration in the product: the AI layer is a core product pillar not a feature.

Hands-On Engineering

• Write production-grade code - much of it through and alongside agents, all of it to your standard (stack to be defined).
• Build and maintain frontend interfaces where needed (stack to be defined). Own database design and query performance
• Design and ship real-time systems: live dashboards, event-driven pipelines.

Product AI & LLM Layer

• Own the end-to-end AI layer of the product (from prototype to production): lead adoption of new LLM tools, build and operate RAG pipelines, manage vector databases, and ensure only production-ready solutions are used.
• Design and orchestrate AI workflows and prompt strategies to power core use cases (guest chat, operator briefings, compliance docs, natural-language commands) while continuously evaluating and integrating cutting-edge AI capabilities.

Integration Layer

• At a certain point own the full integration architecture across all third-party systems - IoT platforms, smart locks, payment rails, government and regulatory APIs.
• Ensure the integration layer is reliable, observable and extensible - future integrations include additional regulatory APIs and secondary trading infrastructure.

Engineering Leadership

• Lead a small, high-caliber hybrid team (engineers + AI agents): set technical standards, run code reviews, unblock delivery, and ensure consistent execution under pressure while maintaining high quality.
• Act as the bridge between business and engineering: translate product needs into clear, agent-executable work, build an AI-first engineering culture, and mentor the team on effectively working with AI (what to delegate vs. retain).

Infrastructure & Reliability

• Own and build scalable infrastructure from scratch: set up CI/CD with agent participation, design cost-efficient cloud architecture and ensure production readiness for live operations.
• Implement full observability and reliability practices: monitoring, alerting, agent traceability, cost/latency tracking, API health and an on-call capable system that is transparent and controllable.

What we are looking for

Must have

• 5-7+ years in software engineering, with technical leadership experience of a team under direct supervision.
• Proven 0 → 1 experience - you have built AI first engineering teams, systems and architecture from scratch, not joined an already-scaled org.
• Strong production experience with modern backend ecosystems (TypeScript / Node.js or equivalent) - you can design and evolve service architectures at speed.
• Solid frontend engineering competence (React, Vue.js or equivalent) - enough to architect, review and unblock teams.
• Deep understanding of data layer design (relational databases such as PostgreSQL or equivalent), including multi-tenant architectures, performance and access control models.
• Proven ability to select, evolve and own the technology stack based on product needs, not trends.
• Comfortable working across the full stack when needed — but with clear architectural judgment on trade-offs
• Daily, deep, native use of agentic coding tools on real production codebases - not toy demos. You have shipped meaningful features where the majority of code was agent-authored under your direction.
• Hands-on experience designing or significantly extending an internal AI development workflow - orchestration of multiple agents, spec-to-PR pipelines, automated review, agent-driven test generation, or comparable systems.
• Production experience with LLM/AI integration in user-facing product - RAG pipelines, vector databases, prompt engineering, agent workflows. Features real users rely on, not demo projects.
• Rigorous instinct for evaluation - you treat LLM outputs as something to be measured, not trusted, and you have built evals to prove it.
• Demonstrable track record of integrating multiple complex third-party APIs into a coherent, stable product.
• Experience building real-time systems
• Comfortable setting up CI/CD and cloud infrastructure from zero.
• Advanced English - oral and written.

Strong advantage (Nice to have)

• You have built or open-sourced an agentic dev tool, orchestrator, eval harness or comparable internal-facing system.
• Familiarity with orchestration frameworks and agent observability tooling
• Experience in PropTech, Fintech, hospitality technology or multi-sided marketplace platforms.
• Background with IoT protocols and smart home device ecosystems.
• Experience integrating government or regulatory APIs.
• Familiarity with tokenization infrastructure or regulated fintech architecture.

Why this role

You will simultaneously build the first AI-native operating system for real estate in Dubai and the AI-first engineering org that ships it. Both are differentiators, both are hard and both are yours.

• Genuine architectural ownership - of the product and of the way we build it. This is not a “maintain and improve” role.
• Clear growth trajectory - this role evolves into Head of Engineering and eventually CTO. We are building that succession deliberately.
• Direct access to founders - short decision loops, no middle management, real influence on product direction.
• Technically ambitious surface area - AI agents, RAG, IoT, real-time systems, government API integrations and eventually (later) tokenization infrastructure. All in one product, all built by a system you design.
• Bonuses - we know how to appreciate the hard work. Bonuses will be assigned based on performance at CEO’s discretion.
• Equity participation - at a defined point you will own a share of what you build.
• Great office in the heart of Dubai’s business life - Once Central Plaza

We are looking for a Clinical LLM Engineer to work on real-world healthcare challenges, building LLM-powered solutions for clinical data extraction.

The platform is scaling across the US healthcare system, focusing on practical impact and improving care through better use of clinical data.

You will fully own prompt engineering and extraction quality, working directly with LLM APIs, while a separate team handles backend and infrastructure. Your focus will be on improving accuracy, system reliability, and adapting workflows as LLM capabilities evolve.

We offer:

• Flexible working hours;
• Paid vacation and sick leave;
• Health insurance;
• Professional growth opportunities;
• Internal English classes & compensation for courses;
• Legal and accounting support.
   

Requirements:

• 3+ years of Python development experience (data processing, scripting, automation);
• Hands-on experience with prompt engineering for LLMs in production;
• Experience working with US healthcare or clinical data;
• Strong understanding of unstructured data (text, PDFs, scanned documents);
• Experience with document classification or similar tasks;
• Experience with evaluation frameworks for LLM performance;
• Basic experience with cloud environments (AWS Lambda, EC2, simple pipelines);
• Experience with Git (GitHub);
• Understanding of Agile development practices;
• High English level.
   

Responsibilities

• Design and optimize prompts for accurate clinical data extraction;
• Adapt prompt strategies to handle real-world variability in medical documents;
• Build document classification workflows (labs, imaging, vaccines, etc.);
• Develop Python pipelines for LLM interaction and data processing;
• Evaluate and improve extraction quality across document types;
• Continuously adapt prompting approaches as LLM capabilities evolve.

We are looking for a Senior AI Engineer / AI Solution Architect to support AI-driven automation and digitalization project.

This role is ideal for someone with strong Python backend experience, hands-on work with LLM-based solutions, AI agents, orchestration frameworks, and Microsoft Azure AI services.

You will work on practical AI solutions for information extraction, process automation, system integrations, and production-ready AI workflows.

What You’ll Do

• Design and develop AI agents
• Build backend services and APIs with Python
• Work with FastAPI or similar Python frameworks
• Implement AI/LLM-based information extraction pipelines
• Build orchestration logic using LangChain, LangGraph, or similar frameworks
• Integrate LLMs into business applications and workflows
• Work with Microsoft Azure AI services
• Develop system integrations and APIs
• Implement asynchronous, queue-based, and event-driven processing
• Support deployment, monitoring, maintenance, and continuous improvement

What We’re Looking For

• Senior or Architect-level experience
• Strong hands-on experience with Python backend development
• Experience with FastAPI or similar backend frameworks
• Experience with LLM integration and AI agents
• Experience with LangChain, LangGraph, or similar orchestration frameworks
• Experience with Microsoft Azure technologies, namely:
  • Azure OpenAI
  • Azure AI Foundry
  • Azure Document Intelligence
  • Azure Blob Storage
  • Azure Storage Queues
• Solid understanding of APIs, system integrations, queues, and event-driven architectures
• Experience with production systems, not only prototypes
• Ability to work independently and take ownership of technical delivery
• Excellent communication skills in English

Nice to Have

• Experience with enterprise system integrations
• Experience with deployment, monitoring, and DevOps operations
• Experience with RAG, embeddings, vector search, or knowledge retrieval solutions
• Experience with CI/CD, Docker, or cloud monitoring tools
• Consulting or stakeholder-facing experience

Application Details

We appreciate applications that closely match the requirements.

To help us evaluate the profile properly, we would appreciate it if the CV clearly shows how and on which projects the required skills were used.

Please include:

• CV in English
• Earliest start date 

We’re looking for an AI Engineer to join our outsourcing team — not a pure ML researcher, but a pragmatic, data-driven backend engineer who knows how to put LLMs, vision APIs, and off-the-shelf models to work inside real products.

Most of our work isn’t training models from scratch — it’s understanding the business logic, collecting and cleaning data, wiring it into LLMs or services like AWS Textract, and shipping the result as a reliable API inside our existing platform.

If you’ve spent the last few years building APIs and integrations, you’re comfortable with data, and you’ve leaned hard into Cursor or Claude Code to deliver projects faster — this is for you.

What you’ll do

• Build and ship LLM-powered features: prompt design, data prep, passing context to the model, parsing and validating output, returning clean APIs.
• Design and implement integrations between our product and third-party AI services (OpenAI, Anthropic, Hugging Face models, AWS Textract, etc.).
• Take document-processing and computer-vision tasks end-to-end: ingest → Textract/vision API → post-process → structured output consumed by our backend.
• Write backend services and APIs in Node.js (our primary backend), dropping into Python when a task calls for it (model work, data scripts, fine-tuning).
• Fine-tune existing models and prompts — not from scratch, but iterating on what’s already in place to get better accuracy, cost, or latency.
• Do the unglamorous but critical work: data collection, cleaning, transformation, pattern-finding — often by letting an LLM do the heavy lifting on structured and unstructured input.
• Maintain and improve existing AI and automation workflows already running in production.
• Monitor cost and performance of model/API usage, propose optimizations, and forecast costs for new features.
• Prepare and present demos and solution overviews to U.S.-based clients.
• Document architecture, prompts, and pipelines in Confluence.

What we’re looking for

• 2+ years shipping production backend systems, with meaningful hands-on experience integrating LLMs or AI APIs into real products.
• Strong in Node.js with the flexibility to work in Python — or a Python engineer who’s comfortable committing Node.js code. We need someone fluent on both sides; pure-Python candidates won’t be a fit.
• Solid grasp of algorithms and data structures — enough to write custom logic when an LLM or library can’t cover the case.
• Real experience with LLM integrations: OpenAI, Anthropic, or similar. Prompt engineering, function/tool calling, structured output, retrieval, evaluation.
• Familiarity with the Hugging Face ecosystem — picking models, running inference, fine-tuning where it makes sense.
• API and integrations background: REST, auth, webhooks, rate limits, retries, idempotency — the stuff that makes integrations not break at 2 a.m.
• Comfortable with data work: collecting, cleaning, transforming, and analyzing data (SQL, pandas, or the Node equivalents).
• Working knowledge of AWS — especially Textract, Lambda, S3, and the services around document and data pipelines. Bonus for Athena, Glue, Kinesis, SageMaker.
• Exposure to NLP and Computer Vision concepts — enough to pick the right tool and evaluate results, not necessarily to train SOTA models.
• Familiarity with CI/CD and deploying AI-powered services to production.
• Experience building chatbot workflows — conversational flows, multi-turn logic, context management — is a plus, as this is among our planned projects.
• AI-native delivery workflow. You use Cursor or Claude Code daily and know how to ship a project with minimal hand-written code — scoping work for the agent, reviewing generated code critically, orchestrating multi-step tasks, and getting to shipped quality faster than a traditional workflow. If you can’t describe how you use these tools to deliver, this role isn’t the right fit.

Nice to have

• Experience fine-tuning open-source LLMs or vision models on domain-specific data.
• Background in fintech, healthcare, or construction domains.
• Experience with vector databases, RAG pipelines, or agentic workflows.

What we offer

• Competitive salary with regular reviews.
• Support for individual entrepreneurs with accounting assistance.
• Fully remote work.
• A clear path for professional development and growth.
• A friendly team environment and engaging team-building activities (online and offline).

We are seeking a Senior Python Developer with AI or ML experience to join our AI & Data project. In this role, you will combine high-end machine learning engineering with a revolutionary approach to software delivery. You will not just build AI; you will build AI using AI, orchestrating agentic workflows to deliver complex solutions at a velocity traditional teams cannot match.

You will focus on building practical, production-ready solutions that bridge the gap between unstructured data and structured logic using LLMs, agentic workflows, and knowledge representations (ontologies, knowledge graphs). You are expected to be an "AI-Native" pioneer, utilizing tools like Claude Code, Cursor, Antigravity, and custom MCP servers to automate your own development lifecycle - from data exploration and model evaluation to code generation and documentation.

Requirements:

• 4+ years of professional experience in software engineering (Python) 
• Proven experience with AI or ML projects, with accountability for end-to-end delivery in a production environment.
• Strong proficiency in Python and the modern AI or ML ecosystem (e.g., PyTorch, Hugging Face, LangChain/LangGraph, Scikit-learn), with a strong foundation in engineering best practices such as code modularity, testing, and version control.
• Hands-on experience with data ingestion, RAG pipeline optimization, model evaluation, deployment (MLOps), and monitoring, including CI/CD pipeline development and containerization using tools like Docker or GitHub Actions.
• Deep understanding of generative AI (LLMs, embeddings, RAG, prompt engineering, and agentic reasoning) and its practical constraints (latency, cost, safety, hallucinations).
• Experience turning complex business needs into "machine-ready" technical specifications and acceptance criteria.
• Evidence of using modern GenAI tools (Claude Code, GitHub Copilot, etc.) to significantly accelerate your development and testing process.
• Good English to work in a multinational team
• Strong problem-solving and follow-up skills; must be proactive and take initiative

Responsibilities: 

• Design, develop, and maintain scalable Python applications and services that integrate AI/ML components.
• Write clean, testable, and efficient code following software engineering best practices
• Implement containerization and deployment workflows using Docker and/or Kubernetes
• Design and implement solutions that combine the reasoning power of LLMs with the precision of structured knowledge (ontologies/knowledge graphs).
• Apply structured 4-phase debugging to ML pipelines, focusing on root-cause analysis of hallucinations, retrieval failures, and data drift.
• Define and automate "Skills" (prompt libraries, evaluation scripts, and deployment templates) to be reused across multiple AI-Native pods.
• Define and implement quality gates, safety metrics, and cost-control practices for GenAI components.
• Work independently on development tasks with a minimal amount of supervision

What is in for You: 

Culture of caring. At GlobalLogic, we prioritize a culture of caring. Across every region and department, at every level, we consistently put people first. From day one, you’ll experience an inclusive culture of acceptance and belonging, where you’ll have the chance to build meaningful connections with collaborative teammates, supportive managers, and compassionate leaders. 

Learning and development. We are committed to your continuous learning and development. You’ll learn and grow daily in an environment with many opportunities to try new things, sharpen your skills, and advance your career at GlobalLogic. With our Career Navigator tool as just one example, GlobalLogic offers a rich array of programs, training curricula, and hands-on opportunities to grow personally and professionally.

Interesting & meaningful work. GlobalLogic is known for engineering impact for and with clients around the world. As part of our team, you’ll have the chance to work on projects that matter. Each is a unique opportunity to engage your curiosity and creative problem-solving skills as you help clients reimagine what’s possible and bring new solutions to market. In the process, you’ll have the privilege of working on some of the most cutting-edge and impactful solutions shaping the world today.

Balance and flexibility. We believe in the importance of balance and flexibility. With many functional career areas, roles, and work arrangements, you can explore ways of achieving the perfect balance between your work and life. Your life extends beyond the office, and we always do our best to help you integrate and balance the best of work and life, having fun along the way!

High-trust organization. We are a high-trust organization where integrity is key. By joining GlobalLogic, you’re placing your trust in a safe, reliable, and ethical global company. Integrity and trust are a cornerstone of our value proposition to our employees and clients. You will find truthfulness, candor, and integrity in everything we do.

About Us
We're a product company building AI-powered solutions for international markets. Our team is lean and fast-moving — we don't wait months to make decisions. We test, analyze, and scale what works. If that's how you naturally operate, keep reading.

The Role
This isn't a portfolio role. You'll measure success in CTR, hook rates, and conversions — and you'll own the full cycle from concept to launch to performance analysis as a core member of our growth team.

Responsibilities
— Produce video ads and static banners for Meta, TikTok, YouTube, and Google with a clear focus on conversion
— Generate several fundamentally different creative directions every week — not variations of the same idea
— Research competitor ads, identify strong mechanics, and build on them to create more effective versions
— Create UGC-style videos that blend naturally into the feed and don't feel like ads
— Use AI as a default — generation, editing, voiceover, characters — not as an occasional shortcut
— Launch hypotheses, read the data, adjust your approach, and repeat
— Occasionally contribute to landing page and presentation design

Requirements
— Strong grasp of performance metrics — CTR, hook rate, ROAS, scroll-stop rate — and how to move them through creative decisions
— Proven experience with video advertising: you know how to stop the scroll in the first 2 seconds and hold attention through to the CTA
— Hands-on with AI tools for image generation, video production, and voice content (not just aware of them — actively using them)
— Able to develop a concept from scratch with minimal briefing — high autonomy is the default here
— Comfortable maintaining high production volume without sacrificing quality

Nice to Have
Experience with AI avatars (HeyGen, Synthesia, D-ID), voice synthesis (ElevenLabs), or any tooling built for scalable UGC production

We're looking for a creative and detail-oriented AI Creator who wants to create video content using AI and come up with scripts for videos that go viral. 

Who are we?

SonderAds is a marketing team that creates viral commercials and develops its own applications. We focus on short videos that grab attention from the very first seconds and help our marketing team achieve outstanding results.

What we expect from you:

• You have at least 6 months of experience as an AI Creator
• You have experience generating video content using AI (Freepik AI, NanoBanana, Veo, Runway, Pika, Kling etc.)
• You are confident with prompt engineering (ChatGPT, Gemini) and know how to achieve high-quality results
• You keep up with the latest AI developments, test tools, and implement the best ones into your work
• Understanding retention hooks, the first 3 seconds of CTR-first, and the performance structure of videos
• You understand trends and the mechanics of viral content
• You quickly test hypotheses and iterate on creative ideas
• You write clear and compelling scripts
• You approach tasks responsibly and handle revisions calmly

Nice to have:

• Experience in the following sectors: Utilities, AI-driven apps, Lifestyle & Wellness, Dating / Social

• Experience editing videos in CapCut / Premiere / After Effects after AI-generated content

   

  Your tasks:

• Help shape and develop the AI direction within the team
• Generate ideas and hypotheses for advertising creatives
• Turn ideas into scripts with a strong hook and clear structure
• Create video content using AI tools 
• Analyze the market and competitors’ approaches, and adapt the best solutions to our needs
• Work with prompts: create, optimize, and structure them

• Set clear and understandable technical specifications for the motion design team 

   

  We offer:

• Paid internship (1 month) — during this time, you will undergo training with practical tasks, get to know the team, and understand whether the format and tasks suit you.
• Remote work. We work quickly, collaboratively, and with a focus on results.
• Interesting projects with strong growth opportunities.
• Schedule: 10:00–19:00 Cyprus time.
• Paid vacation (20 working days) and sick leave.
• 3-month probation period.
• Fixed take-home pay starting from 1,000 USD (depending on your expertise).
• We follow the Cyprus public holiday calendar.
• If you want to turn your love for trends and creativity into a job that brings you joy—apply now! https://career.sonderads.com/vacancy/ai-creator

Project Description:

We are seeking an Expert Blockchain Developer for a short-term, fixed-scope engagement to facilitate a smooth vendor handoff of our blockchain tokenization platform. The system is designed to capture external off-chain data feeds and utilize that data to mint utility and financial tokens. The architecture leverages Ethereum and Polygon (L2) for smart contract execution, and relies on IPFS for storing metadata, slow-moving reporting data, and JSON files.

Responsibilities:

Your primary goal is to ensure a seamless technical transition from the previous development vendor to our new team. You will audit the current Web3 architecture, evaluate the existing smart contracts, and validate the operational approach for the platform's overall blockchain infrastructure
This is a fixed-scope engagement expected to run for a few weeks. Key responsibilities include:
• Smart Contract Code Review: Conduct a comprehensive code review and audit of the existing Solidity smart contracts, including the core ERC-20 token contracts, certificate data structures, and the central minting controller logic.
• Architecture & Approach Evaluation: Assess the overall Web3 architecture. Specifically, evaluate the strategy of storing metadata and large binary object (BLOB) files on IPFS, while rolling up volume-based transactions on the Polygon blockchain.
• Web3 Tooling Assessment: Review, validate, and document the current Hardhat development kit setup to ensure it is ready for the new team to take over.
• Gas Optimization & Operations: Analyze the smart contracts to ensure they are designed with a very low gas footprint. Evaluate the overall operational gas fees associated with the continuous minting and burning of tokens on the network.
• Integration Audit: Evaluate how the blockchain layer interacts with the system's centralized off-chain services, such as the backend APIs and cloud-managed blockchain nodes.

Mandatory Skills Description:

• Extensive professional experience as a Blockchain Developer specializing in Ethereum (L1) and Polygon (L2) network ecosystems.
• Proven track record working with ERC-20 fungible token standards, including implementing customized minting, burning, and access-control mechanisms.
• Strong hands-on experience using Hardhat as a Web3 development, testing, and deployment environment.
• Deep expertise in writing, auditing, and securely deploying Solidity smart contracts.
• Strong ability to audit code for security vulnerabilities, analyze operational gas costs, and recommend or implement architectural optimizations.
• Demonstrated understanding of decentralized storage, specifically utilizing IPFS for handling JSON metadata and large files.

Nice-to-Have Skills Description:

• Domain knowledge of tokenizing Real-World Assets (RWA) or integrating off-chain industrial data feeds.
• Familiarity with cloud infrastructure, specifically managed blockchain services and serverless computing (e.g., AWS Managed Blockchain, Lambda).
• Understanding of data privacy techniques in Web3, such as utilizing encryption protocols for private IPFS data or implementing Zero Knowledge Proofs (ZKP).
• Familiarity with the broader technological stack commonly utilized alongside Web3 platforms (e.g., ReactJS, Node.js, Python, PostgreSQL, Terraform, Docker).