Jobs ML / AI

🚀 Project Description

Facie is an early-stage AI product working with face image analysis.

We are looking for a strong Junior Computer Vision / ML Engineer to build a reliable mechanism for measuring facial geometry from photos.
 

The first challenge is straightforward to describe but non-trivial to solve: given a face photo, accurately measure numerical parameters of different facial features, such as eye dimensions, mouth dimensions, nose geometry, jaw proportions, distances between facial landmarks, and other geometric characteristics.
 

This is a greenfield CV problem.

You will not receive a predefined model or a detailed list of experiments to execute. We expect you to explore several possible approaches, quickly validate them, discard what does not work, and find a solution that is good enough to move into the product.
 

At phase 1 - our engineering philosophy is simple:

20% of effort that delivers 80% of the result is often better than spending weeks searching for theoretical perfection.
 

✅ You are:
 

• Confident with Python
• Understand core Machine Learning concepts
• Have practical experience with Computer Vision OR can demonstrate serious interest in the field
• Can work with existing open-source models and libraries
• Comfortable reading unfamiliar code and quickly running existing projects
• Understand basic model inference and API concepts
• Able to turn an unclear problem into several testable hypotheses
• Comfortable when the first approach does not work
• Able to explain how you would validate whether an experiment actually works
• Focused on finding a practical solution rather than endlessly optimizing one approach
• Comfortable using Git and working with an engineering team

Commercial Computer Vision experience is not required.
 

If your primary background is general ML or software engineering, we would still like to talk if you can demonstrate genuine interest in CV through things such as:

• university or online CV courses
• pet projects
• GitHub projects
• Kaggle
• research or thesis work
• reproduced papers
• personal experiments
   

➕ Will be a plus:
 

• OpenCV
• PyTorch or TensorFlow
• MediaPipe or other face landmark solutions
• Experience with face detection, landmarks or segmentation
• Understanding of 2D / 3D geometry
• Experience reading and implementing research papers
• Docker
• Model serving or inference pipelines
• Experience exposing ML functionality through an API
• Experience designing reproducible ML experiments
• Experience with Cursor, Claude Code, Codex or similar AI development tools
   

♟️ What We Expect from You:
 

• Experiment-first thinking - generate several possible approaches instead of betting everything on the first idea
• 80/20 mindset - optimize for time-to-market and find the simplest solution that provides enough accuracy for the product
• Ownership - do not wait for someone to define every next experiment for you
• Validation mindset - always ask how we know that a result is actually correct, especially when perfect ground truth does not exist
• Fast iteration - prototype, measure, learn, discard weak approaches and move forward
• Engineering judgment - understand when ML is needed and when deterministic geometry or conventional code is a better solution
• AI adoption - actively use modern AI coding tools when they help you iterate faster
• AI skepticism - understand and verify AI-generated code instead of blindly trusting it
• Clear communication - explain what you tried, what failed, what worked and what you recommend trying next
   

🔑 Responsibilities:
 

• Research different approaches for measuring facial geometry from images
• Build quick prototypes and experiments
• Evaluate existing Computer Vision models and open-source solutions
• Compare multiple approaches using measurable criteria
• Design practical validation methods when perfect ground truth is unavailable
• Analyze failure cases and identify why particular approaches fail
• Select solutions based on accuracy, complexity and time-to-market
• Build a reproducible facial geometry measurement pipeline
• Document experiments, conclusions and technical decisions
• Prepare successful solutions so they can be integrated by Software Engineers
• Ideally, help turn successful prototypes into an inference service or API
• Proactively suggest the next experiments instead of waiting for detailed tasks
   

🤖 AI-assisted Engineering
 

We actively use modern AI development tools.

You are welcome to use Cursor, Claude Code, Codex or similar tools to write code, explore libraries, integrate models and accelerate experiments.

We do not care whether every line of code was written manually.

We do care whether you understand:

• what you are testing
• why you selected a particular approach
• whether the result can be trusted
• how you validated it
• what the generated code actually does
• what you would try next if the approach fails
   

🍩 What We Offer:
 

• Part-time or Full-time depending on the candidate
• Remote work
• A real Computer Vision problem with direct impact on the product
• Significant ownership of the CV direction
• Freedom to experiment with different technologies and approaches
• Access to paid AI development tools where needed
• Direct communication with the founder and engineering team
• Opportunity to build a Computer Vision system from the greenfield stage into production
• Opportunity to grow from Strong Junior toward independently owning an ML / CV product area
   

🗣 Recruitment Process:
 

Intro Interview → Live Problem-Solving Session → Small Practical Experiment → Final Interview
 

💻 Live Problem-Solving Session (Optional)
 

This is not LeetCode and not a theoretical ML exam.

You will receive a previously unseen Computer Vision problem and will be asked to think aloud and visualize your approach using a whiteboard, Paint, FigJam or a similar tool.

We want to understand:

• how you decompose an unclear problem
• how many reasonable approaches you can generate
• what you would test first
• how you prioritize experiments
• how you validate results
• what you do when the first few approaches fail
• when you decide that a solution is good enough to ship
   

🧪 Practical Experiment (Optional)

Selected candidates will receive a small Computer Vision experiment.

You can use:

• AI coding tools
• Google
• documentation
• open-source models
• existing libraries
• research papers

We are not testing your ability to code without assistance.
 

We are testing your ability to turn an ambiguous CV problem into a working and validated solution quickly.
 

The expected output is a small working prototype plus a short explanation of:

• approaches considered
• approach selected
• why it was selected
• how the result was validated
• discovered limitations or failure cases
• what you would try next with one additional day

We are looking for an AI Product Engineer who can turn business problems into working digital solutions using modern AI tools, LLMs, automation platforms, and AI-assisted development workflows.

This is not a traditional Backend, Frontend, or Machine Learning Engineer position.

The role is designed for a technical AI generalist who can quickly understand a business need, validate an idea, build a functional prototype or MVP, and collaborate with specialized engineers and designers to bring the solution to production quality.

What you will do

• Analyze business processes and identify opportunities for AI automation and optimization.
• Turn business requirements into functional prototypes, MVPs, and internal tools.
• Build AI-powered web applications, dashboards, workflows, integrations, and product features.
• Use AI-assisted development tools such as Claude Code, Cursor, Codex, OpenAI, Anthropic, and similar platforms.
• Design and implement solutions using LLM APIs, AI agents, automation tools, and third-party services.
• Build end-to-end proof-of-concept solutions across different technologies when needed.
• Evaluate whether a task should be solved with custom development, AI agents, automation platforms, or a combination of approaches.
• Optimize prompts, context usage, token consumption, model selection, and AI-related costs.
• Test hypotheses quickly and validate whether a solution creates real business value.
• Prepare prototypes for further review and refinement by specialized developers, designers, or other domain experts.
• Document solution logic, limitations, risks, and recommendations for further development.

• Collaborate closely with product managers, engineers, designers, and company leadership.

   

What this role is about

The main goal of this position is not to develop one narrow technical area in depth.

The goal is to use AI as a force multiplier to:

• reduce development time;
• automate repetitive work;
• lower operational costs;
• validate product ideas faster;
• create tools that improve business performance;
• build functional solutions before involving a full specialized team.

You should be comfortable moving between different types of tasks and technologies. One project may involve an internal HR automation tool, another may be a sales workflow, an AI assistant, a web platform, or a mobile application prototype.

You are not expected to replace senior specialists in every area. You are expected to build a strong functional foundation that can later be reviewed, improved, and productionized by domain experts.

Requirements

• Strong technical foundation in software development, computer science, or a related field.
• Commercial software development experience with Python, JavaScript, TypeScript, or similar technologies.
• Practical experience building complete applications, prototypes, integrations, or automation solutions.
• Confident use of AI coding tools in real development workflows.
• Hands-on experience with OpenAI, Anthropic, Gemini, or other LLM APIs.
• Understanding of prompt engineering, context management, token usage, and model limitations.
• Experience designing AI agent or multi-step automation workflows.
• Ability to translate an unclear business problem into a structured technical solution.
• Ability to work across unfamiliar technologies and quickly learn new tools.
• Understanding of APIs, databases, authentication, integrations, and basic system architecture.
• Strong problem-solving skills and a product-oriented mindset.
• Ability to balance development speed with code quality, security, and maintainability.

• English level sufficient for working with technical documentation and participating in project communication.

   

Nice to have

• Experience with RAG systems, embeddings, vector databases, and document processing.
• Experience building AI agents and multi-agent systems.
• Experience with n8n, Make, Zapier, or other workflow automation tools.
• Startup, product discovery, hackathon, or MVP development experience.
• Experience working directly with business stakeholders or clients.
• Understanding of AI solution economics, including token costs, infrastructure costs, and expected business value.

The most important criterion is not the number of AI tools listed in your CV. We are looking for someone who can demonstrate how AI helped them deliver useful, functional solutions significantly faster and create measurable value for a business

About Our Client

Our client is a leading enterprise data platform company building an open, high-performance data lakehouse for AI and analytical workloads. The platform combines an intelligent SQL query engine, an AI-ready semantic layer, and an open catalog built on Apache Iceberg — enabling Fortune 500 companies across finance, energy, manufacturing, and logistics to unify, query, and govern data at massive scale across cloud and on-premise sources.

About the Role

We are looking for a Senior Software Engineer to build and operate production AI agent and search services on top of a large-scale data platform. This is hands-on work at the intersection of distributed backend engineering and applied AI: multi-agent workflows, tool-execution infrastructure, retrieval and relevance, and integrations with multiple LLM providers — all running as real, customer-facing production services with the reliability expectations that implies.

Responsibilities

• Design and implement scalable multi-agent workflows (including conversation state), tool-execution infrastructure, and data-aware tools working with catalogs, schemas, lineage, SQL, jobs, semantic metadata, data preparation, and visualizations
• Build search and retrieval capabilities with OpenSearch or equivalent — indexing, relevance tuning, hybrid keyword + vector search
• Integrate multiple LLM/model providers with secure configuration and graceful degradation
• Develop APIs and event contracts across REST, streaming/SSE, gRPC, protobuf, and SDKs, including UI integrations
• Operate, monitor, and improve production services — service health, logs, metrics, traces, search-cluster health, latency, and error rates; participate in the team's production-support model
• Investigate incidents, drive root-cause analysis, and ship durable fixes
• Design for permissions, tool approvals, multi-tenancy, and customer-data governance
• Maintain dependencies, apply security fixes, and reduce tech debt; produce designs, tests, runbooks, and documentation; lead technical discussions and review code

Required Qualifications

• B.S. or M.S. in Computer Science, Computer Engineering, or a related field — or equivalent practical experience
• 7+ years of relevant experience, or equivalent demonstrated senior-level impact
• Strong Java software engineering skills
• Strong grasp of concurrency, data structures, API design, testing, maintainability, and backward compatibility
• Solid background in distributed systems, microservices, cloud services, or data-intensive backends
• Hands-on experience with search technologies — OpenSearch, Elasticsearch, or Lucene — including vector search, embeddings, or relevance systems
• Experience building LLM applications, agent/tool workflows, RAG systems, or model-provider integrations
• Strong production instincts: diagnosing failures via logs, metrics, and traces; designing for fault tolerance, retries, cancellation, and recovery
• SQL and familiarity with data platform concepts: catalogs, metadata, schemas, governance, lineage
• Comfort leading ambiguous, cross-service work with clear stakeholder communication and strong written documentation
• Comfortable with AI-assisted development workflows — using modern AI tools productively while critically validating their output
• English Upper-Intermediate or higher (B2+) — daily written and verbal communication with a US-based engineering team
• Availability to work EU business hours shifted 2–3 hours later for daily overlap with US West Coast mornings

Desired Skills

• LangChain4j or similar agent frameworks
• Python for AI services, evaluation harnesses, or sandboxed execution
• React and TypeScript
• gRPC, protobuf, Quarkus, Kubernetes, MongoDB, KV stores, event-driven architectures
• Apache Arrow, Apache Iceberg, OpenLineage, semantic layers, or data-governance systems
• AI quality evaluation: LLM-as-judge, model benchmarking, production AI metrics
• OpenSearch operations: index lifecycle management, relevance tuning, incident response
• Open-source contributions

Details

• Engagement: Long-term contract
• Location: Europe (EU / EEA / UK), remote
• Working hours: EU business hours, shifted 2–3 hours later for daily overlap with the US West Coast team

Mirko Solutions is an international IT company specializing in web and mobile development for clients across the US, Canada, EU, and Australia. We are growing rapidly and are looking for a Middle\Senior AI Engineer to join our team and drive complex, high-impact projects.

Job Requirements:

• 3+ years of experience deploying machine learning models (classical ML and/or LLMs) in cloud environments (AWS/GCP/Azure) using containers and Kubernetes
• Hands-on experience with MLOps tools such as MLflow, Kubeflow, SageMaker, Vertex AI, Feast, or equivalent
• Proven experience building robust data/feature pipelines and implementing monitoring for model drift and performance
• Strong Software Engineering fundamentals: version control, automated testing, CI/CD, security, and cost-aware development
• Excellent collaboration and communication skills in  English 
• Ownership mindset, curiosity, and a bias for action in a fast-paced environment

Responsibilities:

• Design, implement, and maintain end-to-end ML pipelines for both classical ML and LLM-based solutions
• Deploy and manage models in cloud environments (AWS / GCP / Azure) using containers and Kubernetes
• Apply MLOps best practices for reproducibility, automation, and monitoring
• Build reliable data/feature pipelines and implement real-time monitoring for model drift, latency, and performance tracking
• Actively contribute to engineering excellence through CI/CD, testing, security, and cost optimization

Nice to have:

• Experience with deep learning frameworks such as PyTorch or TensorFlow
• Understanding of distributed systems (Spark, Ray)
• Experience working with feature stores and data governance

We provide the following for our employees:

• Competitive salary according to qualification
• Comfortable working environment
• Experienced colleagues
• Opportunity to work with interesting projects,
• Regular performance reviews
• Friendly atmosphere, care for the comfort of professionals

We are looking for an AI Engineer with practical experience in robotics, simulation, synthetic data and AI agents.

The first priority for this role is to understand how our 3D, simulation and configurator expertise can be useful for robotics teams: what training data they need, how synthetic data can help, where real-world data is required, and which product hypotheses are worth testing.

You will work at the intersection of AI, robotics, 3D/simulation and production software engineering. We expect you to be able to move from an unclear problem to research, technical discovery, prototype, evaluation and a clear recommendation for the next step.

Responsibilities:

• Analyze our current 3D/simulation projects and identify possible use cases for robotics.
• Understand data requirements for training and evaluating robotics models.
• Define where synthetic data, 3D scenes, procedural generation and simulation can create value.
• Build prototypes and experiments for selected robotics or AI scenarios.
• Design and implement AI-agent systems around LLMs, tools, APIs and internal data.
• Integrate AI models into working services, pipelines and tools.
• Set up evaluation, logging, monitoring and feedback loops for AI systems.
• Work with developers, 3D artists, product stakeholders and potential users.

Requirements:

• 3+ years of software engineering experience.
• Strong Python skills and experience building backend services, APIs or ML systems.
• Practical experience with robotics, robotic simulation, autonomous systems or related domains.
• Experience with synthetic data, simulation environments, 3D/game engines or data generation pipelines.
• Understanding of ML data lifecycle: collection, generation, labeling, validation, versioning and evaluation.
• Experience integrating LLMs or AI models into real products or internal tools.
• Experience with AI agents: tool calling, API integration, RAG, context/state management, retries and fallback logic.
• Ability to deploy and operate AI services using Docker, cloud or similar infrastructure.

Nice to have:

• ROS/ROS2, Isaac Sim, MuJoCo, Gazebo, Unity, Unreal Engine or Blender.
• Camera/LiDAR/depth/segmentation datasets.
• Domain randomization, Sim2Real, reinforcement learning or imitation learning.
• LangGraph, LangChain, LlamaIndex, CrewAI or custom agent orchestration.
• PyTorch/TensorFlow, fine-tuning, model evaluation or ML experiment tracking.
• Experience in game development, VFX, 3D pipelines or digital twins.

In the first 30 days, we expect you to understand our project context, analyze possible robotics use cases, describe data requirements and propose several product hypotheses.

By 60 days, we expect a working prototype or technical experiment, clear evaluation criteria, documented findings and a recommendation on whether to continue, change direction or stop the selected hypothesis.

We are looking for a senior engineer to own the quality of our AI features and help define engineering standards across the team.

Approximately 70% of this role focuses on quality and evaluation for agentic workflows: building evaluation harnesses, maintaining datasets, implementing regression gates, and turning production failures into repeatable checks.

The remaining 30% focuses on improving product engineering through code reviews, resilient design, mentoring, and early involvement in feature development. You will also contribute production code to stay close to the systems you review.

This role combines software engineering, AI evaluation, and technical leadership. It requires broader ownership than a traditional test automation position.

Our Stack

• Languages: TypeScript and JavaScript
• Backend: Node.js with Express
• Frontend: React and React Native
• Databases: PostgreSQL and MongoDB
• Infrastructure: AWS
• Testing: Playwright for web and Maestro for mobile
• CI/CD: GitHub Actions

Responsibilities

AI Evaluation & Quality Engineering - approximately 70%

• Build and maintain evaluation harnesses, golden datasets, and scoring methods for production agentic workflows.
• Define measurable quality standards for AI features, including task success, failure handling, latency, and cost.
• Implement regression gates in CI so changes receive an evaluation verdict before merging.
• Own the Playwright web and Maestro mobile end-to-end suites, keeping them fast, reliable, and transparent about failures.
• Establish engineering standards for code reviews, architectural patterns, and targeted refactoring.
• Instrument AI features in production and turn observed failures into new evaluation cases.
• Investigate evaluation regressions and help the team determine whether changes are ready to ship.

Product Engineering & Resilience - approximately 30%

• Review code across Node.js, React, and React Native applications, providing specific, actionable feedback.
• Coach engineers on error handling, retries, idempotency, failure isolation, and tests that demonstrate resilient behavior.
• Participate in feature design early to address quality, testability, and operational risks before implementation.
• Make targeted contributions to production code to maintain hands-on knowledge of the systems.
• Help troubleshoot production incidents by reading traces, reproducing failures, and driving issues to resolution, including occasional incidents outside regular working hours.

Required Experience

• 5+ years of experience building and operating production web applications.
• Strong JavaScript and TypeScript skills, with a deep understanding of runtime behavior.
• Hands-on production experience with Node.js (Express) and React.
• Practical PostgreSQL expertise, including schema design for read patterns, indexing, query plan analysis, and migrations under load.
• Production experience with AWS, including ECS or Lambda, Secrets Manager, CloudWatch, and IAM, with an understanding of infrastructure costs.
• Experience owning and maintaining a Playwright or equivalent automated test suite.
• Experience building and optimizing CI/CD pipelines in GitHub Actions.
• A demonstrated track record of improving code quality through reviews, architectural practices, and successfully delivered refactors.
• Experience mentoring engineers, with concrete examples of practices you helped a team adopt.
• Strong debugging skills and the ability to investigate issues across application code, databases, and infrastructure.
• Clear, effective asynchronous written communication.

AI Engineering & Evaluation - Required

Hands-on AI engineering and evaluation experience is essential. Candidates should be prepared to discuss specific systems, decisions, and outcomes.

• Daily experience working with frontier models and agentic coding tools such as Claude Code, Codex, or Cursor.
• Experience personally building evaluations for an LLM or agent system, including defining what to score, choosing scoring methods, and responding to changes in results.
• Experience constructing and maintaining evaluation datasets: sourcing cases, managing labeling, and keeping coverage relevant as the product evolves.
• Understanding of agentic failure modes that conventional unit tests do not capture.
• A repeatable approach to providing agents with context through instruction files, tool definitions, MCP servers, and subagent roles.
• A practical approach to tracking token spend and wall-clock time per unit of delivered work.

US Company is searching for a Middle AI Support Engineer to join an innovative product team developing an AI-powered SaaS platform. This is an exciting opportunity to work with modern cloud technologies, Large Language Models (LLMs), and scalable web applications in a distributed international team. Full-time, official contract, remote work, and US business hours (9am-5pm, CT).

Brief project description:
The product is SaaS, which enables businesses to automate and enhance customer communications through AI-powered workflows and modern communication technologies.

Responsibilities:

• Triage and analyze incoming tickets, identifying bugs, feature requests, existing functionality, and configuration issues.
• Investigate issues, troubleshoot AI workflows, and provide clear, accurate responses to users.
• Improve and maintain AI prompts and instructions to enhance response quality and reliability.
• Make targeted Node.js/TypeScript changes within existing AI workflows and integrations.
• Test and validate prompt, workflow, and code changes before release.
• Escalate complex issues to Product or Engineering and identify recurring issues that could be addressed through product or workflow improvements.

Required skills (must have):

• 3+ years Node.js/TypeScript.
• Hands-on experience with LLMs and prompt engineering.
• Experience debugging AI workflows / AI-powered applications.
• Strong ticket triage and troubleshooting skills.
• Ability to distinguish bugs, feature requests, existing functionality and configuration/usage issues.
• Excellent written and spoken English.
• Strong analytical and problem-solving skills.
• High level of autonomy.

Would be considered as a plus:

• RAG / vector databases.
• Function/tool calling and structured LLM outputs.
• AWS/serverless.
• SaaS/B2B experience.
• Jira/Zendesk/Redmine.
• Experience building AI agents or AI support automation.
• SQL and API integration experience.

Work conditions:

• 100% remote work.
• Full-time (40 hours per week).
• Official contract: salary, sick-leave days, holidays, vacations.
• US business hours: 9am-5pm, CT.

Interviewing / Hiring process:
Step 1 - preliminary interview (main questions) - 45 mins
Step 2 - internal technical interview - 60 mins
Step 3 - technical interview with Team Leader - 60 mins

N-iX is a global software development company founded in 2002, connecting over 2,400+ tech professionals across 40+ countries. We deliver innovative technology solutions in cloud computing, data analytics, AI, embedded software,IoT, and more to global industry leaders and Fortune 500 companies. Join us to create technology that drives real change for businesses and people across the world.

Our client is a fast-growing European fintech company in the business spend management space — corporate cards and related financial products — serving SME and mid-sized business customers across the EU and UK, in a regulated environment with GDPR compliance obligations. Engineering is organized into cross-functional squads, with platform/enabling teams providing shared tooling horizontally. The client already runs an AI-native engineering practice: Claude Code and GitHub Copilot are used daily, supported by a growing library of shared, versioned Skills embedded in key repositories, enabling an end-to-end flow from ticket to implementation, testing and PR in several codebases. AI tool/connector rollout follows an approved-list and pilot process. The client is AWS-first overall; for data platform and analytics workloads it also runs GCP, with BigQuery as the primary data warehouse. Day-to-day coordination is Slack-first, with Linear for ticket tracking, GitHub for code/PR review, and Notion as the knowledge base.

The client is also building out its AI platform and agentic capabilities: it recently launched an MCP surface in closed beta, giving external AI assistants a structured way to connect and perform real workflows behind guardrails, and treats agent reliability as a system property (tool contracts, approval/consent gates for write actions, evaluation harnesses).

We're looking for a Senior AI Platform Engineer to design, build and operate the shared GenAI infrastructure that product teams rely on.

Key Responsibilities:

• Design, build and operate shared GenAI infrastructure: LLM routing, vector search and RAG infrastructure, MCP gateway, and AI observability/evaluation tooling.
• Apply strong distributed-systems fundamentals: async workflows, idempotency, failure design.
• Work hands-on with LLM APIs in production.
• Apply an AI-security mindset: prompt injection defenses, PII-in-logs handling, credential handling.
• Apply real engineering rigor to the Context Development Lifecycle (CDLC): generate, evaluate, distribute and observe the context that powers AI agents.
• Multiply the output and quality of the squad you join, and share patterns/practice beyond your immediate team so adoption compounds across the organisation.
• Embed directly into a client squad as a hands-on Individual Contributor (not a coaching/managerial role).

Must-Have Skills:

• Kotlin or Python as primary proficiency, with comfort contributing to both.
• Experience designing/building/operating shared GenAI infrastructure: LLM routing; vector search and RAG infrastructure; MCP gateway; AI observability and evaluation tooling.
• Strong distributed-systems fundamentals: async workflows, idempotency, failure design.
• Hands-on production experience with LLM APIs.
• AI-security mindset: prompt injection, PII in logs, credential handling.
• Agent & harness engineering fluency, with concrete evidence of building/operating this kind of tooling, not just using it.
• Comfortable with the client's current daily tools: Claude Code and GitHub Copilot.

Nice-to-Have Skills:

• Specific cloud depth (AWS and/or GCP), Grafana, or named LLM API vendors. The RFP describes these capabilities generically rather than naming specific tools for this role — listed here as plausible, not confirmed.

About the client

Our customer is the European online car market, serving over 30 million monthly users and present in 18 countries. As part of their project, they are building an internal AI platform and are looking for a Senior AI Engineer with genuine, hands-on experience building agentic AI systems - not just integrating existing tools.

This is a hands-on engineering role for someone who has real depth in both AI system design and AWS platform engineering, and who can move fluidly between the two to build production-grade, agentic solutions.

While this is a hands-on role, you will also influence technical direction, raise the bar for engineering practices, and enable other data scientists and engineers to succeed.

Duration is 4-6 months with the possibility of prolongation. 

Time zone: EU or Canadian time zone.

We are ready to consider candidates for part-time cooperation.

Responsibilities:

• Design, build, and maintain agentic AI systems as part of the AI platform
• Work in depth with AWS to build and operate the underlying platform infrastructure
• Design and implement knowledge graph solutions to support AI reasoning and retrieval (e.g. using AWS Neptune or Neo4j)
• Collaborate with cross-functional teams to align the AI platform with business goals and internal use cases
• Troubleshoot and resolve issues across integrated systems to ensure reliable, end-to-end agentic workflows.

Requirements:

• 5+ years of experience in Software Development
• Real, hands-on experience building agentic AI systems - genuine understanding of how they work, beyond just using existing tools or frameworks off the shelf.
• Strong, in-depth AWS experience - real platform engineering depth, not incidental or side use of AWS.
• Strong Python knowledge
• Deep experience building knowledge graphs, ideally with AWS Neptune or Neo4j - especially valuable for this role.
• Experience with LLMs, prompt engineering, and AI integration patterns.
• Strong troubleshooting skills and a collaborative, team-first mindset.
• English level - upper-intermediate (both verbal and written)

Nice to Have:

• Familiarity with MCP (Model Context Protocol).
• Proficiency in infrastructure as code (e.g. CDK in TypeScript/Node.js) to manage AWS services such as Amazon Bedrock and Agent Core.
• Docker/Kubernetes familiarity.

We offer*:

• Flexible working format - remote, office-based or flexible
• A competitive salary and good compensation package
• Personalized career growth
• Professional development tools (mentorship program, tech talks and trainings, centers of excellence, and more)
• Active tech communities with regular knowledge sharing
• Education reimbursement
• Memorable anniversary presents
• Corporate events and team buildings
• Other location-specific benefits

*not applicable for freelancers

Are you a Data Scientist with a love of LLMs, generative AI?

We are looking for a passionate Data Scientist to implement AI solutions aimed at achieving business goals.

This role offers the opportunity to work on cutting-edge AI adoption projects that helps to improve current business processes.
 

     You'll be a great fit if you have:

•  Strong Python Experience (2 year +);
• Experience with LLM , Diffusion models;
• Knowledge of Prompt engineering;
• Experience with Gen AI-related technologies such as LangChain and RAG;
• Experience with Neural Networks (Optional) ;
• Experience with NLP , Predictive analytics and Machine learning;
• Experience with Pandas;
• Experience with SQL, including experience with large datasets;
• Strong experience in statistics;

• Bachelor's degree in Computer Science or a related field.
   

  What you'll do:

• Develop AI agents that utilize LLM, RAG and langchain approach;
• Implement LLM and Diffusion models to boost business productivity;
• Utilize LLM (LLM Vision) to improve object detection, text classification and extraction;
• Create forecasting, recommendation, and classification models;
• Transform business challenges to AI applications.
   

     We ensure your growth with:

• Competitive salary fixed in USD;
• Flexible working schedule and fully remote work format;
• Paid vacation days and sick leave days ;
• Personal and professional development opportunities;
• Participation in building innovative projects from scratch using modern technologies;
• Team-building activities and corporate events;
• English classes and educational events.

About Our Client

Our client is a leading enterprise data platform company building an open, high-performance data lakehouse for AI and analytical workloads. The platform combines an intelligent SQL query engine, an AI-ready semantic layer, and an open catalog built on Apache Iceberg — enabling Fortune 500 companies across finance, energy, manufacturing, and logistics to unify, query, and govern data at massive scale across cloud and on-premise sources.

About the Role

We are looking for a Senior Software Engineer to build and operate production AI agent and search services on top of a large-scale data platform. This is hands-on work at the intersection of distributed backend engineering and applied AI: multi-agent workflows, tool-execution infrastructure, retrieval and relevance, and integrations with multiple LLM providers — all running as real, customer-facing production services with the reliability expectations that implies.

Responsibilities

• Design and implement scalable multi-agent workflows (including conversation state), tool-execution infrastructure, and data-aware tools working with catalogs, schemas, lineage, SQL, jobs, semantic metadata, data preparation, and visualizations
• Build search and retrieval capabilities with OpenSearch or equivalent — indexing, relevance tuning, hybrid keyword + vector search
• Integrate multiple LLM/model providers with secure configuration and graceful degradation
• Develop APIs and event contracts across REST, streaming/SSE, gRPC, protobuf, and SDKs, including UI integrations
• Operate, monitor, and improve production services — service health, logs, metrics, traces, search-cluster health, latency, and error rates; participate in the team's production-support model
• Investigate incidents, drive root-cause analysis, and ship durable fixes
• Design for permissions, tool approvals, multi-tenancy, and customer-data governance
• Maintain dependencies, apply security fixes, and reduce tech debt; produce designs, tests, runbooks, and documentation; lead technical discussions and review code

Required Qualifications

• B.S. or M.S. in Computer Science, Computer Engineering, or a related field — or equivalent practical experience
• 7+ years of relevant experience, or equivalent demonstrated senior-level impact
• Strong Java software engineering skills
• Strong grasp of concurrency, data structures, API design, testing, maintainability, and backward compatibility
• Solid background in distributed systems, microservices, cloud services, or data-intensive backends
• Hands-on experience with search technologies — OpenSearch, Elasticsearch, or Lucene — including vector search, embeddings, or relevance systems
• Experience building LLM applications, agent/tool workflows, RAG systems, or model-provider integrations
• Strong production instincts: diagnosing failures via logs, metrics, and traces; designing for fault tolerance, retries, cancellation, and recovery
• SQL and familiarity with data platform concepts: catalogs, metadata, schemas, governance, lineage
• Comfort leading ambiguous, cross-service work with clear stakeholder communication and strong written documentation
• Comfortable with AI-assisted development workflows — using modern AI tools productively while critically validating their output
• English Upper-Intermediate or higher (B2+) — daily written and verbal communication with a US-based engineering team
• Availability to work EU business hours shifted 2–3 hours later for daily overlap with US West Coast mornings

Desired Skills

• LangChain4j or similar agent frameworks
• Python for AI services, evaluation harnesses, or sandboxed execution
• React and TypeScript
• gRPC, protobuf, Quarkus, Kubernetes, MongoDB, KV stores, event-driven architectures
• Apache Arrow, Apache Iceberg, OpenLineage, semantic layers, or data-governance systems
• AI quality evaluation: LLM-as-judge, model benchmarking, production AI metrics
• OpenSearch operations: index lifecycle management, relevance tuning, incident response
• Open-source contributions

Details

• Engagement: Long-term contract
• Location: Europe (EU / EEA / UK), remote
• Working hours: EU business hours, shifted 2–3 hours later for daily overlap with the US West Coast team

We are expanding our talent pool of Python Machine Learning Engineers to support upcoming international projects across various industries, including FinTech, Healthcare, Retail, Manufacturing, and SaaS.

While there is no immediate project assignment, selected candidates will become part of our network and will be among the first to be considered when new opportunities matching their expertise become available.

Our machine learning projects typically involve designing, training, deploying, and optimizing predictive models, recommendation systems, computer vision, NLP, and other AI-driven solutions using modern Python technologies and MLOps practices.

We are expanding our talent pool of Python AI Engineers (LLM & GenAI) to support upcoming international projects focused on Generative AI, Large Language Models, AI Agents, and intelligent automation.

While there is no immediate project assignment, selected candidates will become part of our network and will be among the first to be considered when new AI opportunities matching their expertise become available.

Our AI projects typically involve designing and developing LLM-powered applications, Retrieval-Augmented Generation (RAG) systems, AI Agents, intelligent workflows, and enterprise AI solutions using modern Python technologies.

PwC is a global network of more than 370,000 professionals in 149 countries that turns challenges into opportunities. We create innovative solutions in audit, consulting, tax and technology, combining knowledge from all over the world.

PwC SDC Lviv, opened in 2018, is part of this global space. It is a place where technology is combined with team spirit, and ambitious ideas find their embodiment in real projects for Central and Eastern Europe.

What do we guarantee?

• Work format: Remote or in a comfortable office in Lviv — you choose.
• Development: Personal development plan, mentoring, English and Polish language courses.
• Stability: Official employment from day one, annual review of salary and career prospects.
• Corporate culture: Events that unite the team and a space where everyone can be themselves.

About the Role

We are looking for an enthusiastic AI professional who is passionate about exploring and applying Artificial Intelligence to real business challenges.
The successful candidate will work closely with the AI Tech Lead and will take ownership of individual AI initiatives from requirements gathering through solution delivery. The role offers an opportunity to work with cutting-edge AI technologies, experiment with new tools, and help transform business processes through automation and innovation.
This position is ideal for someone who follows developments in AI, enjoys testing new technologies, and wants to build practical AI solutions that deliver measurable value.

Key Responsibilities

• Independently manage and deliver one or more AI-related projects.
• Work with stakeholders to understand business needs and identify opportunities for AI adoption.
• Design and implement AI solutions leveraging technologies such as Prompt Engineering, AI Agents, Retrieval-Augmented Generation (RAG), workflow automation, and Generative AI models.
• Create, test, and optimize prompts for different AI use cases.
• Evaluate and experiment with new AI tools, models, and capabilities.
• Support solution design, testing, and implementation activities.
• Coordinate and direct the work of junior team members assigned to the project.
• Define tasks, distribute workload, review deliverables, and support junior colleagues in their development.
• Contribute to reusable AI components, best practices, and internal knowledge sharing.
• Participate in proof-of-concept development and pilot initiatives.
• Help drive innovation and identify opportunities for new AI solutions across the business.

What We Are Looking For

• Genuine interest and passion for Artificial Intelligence.
• English B2+.
• Approximately 2 years of hands-on experience working with AI tools, AI products, or AI-powered solutions.
• Practical experience with: Generative AI tools and Large Language Models (LLMs); Prompt engineering; AI assistants and AI agents; Retrieval-Augmented Generation (RAG);Workflow automation.
• Ability to work independently and take ownership of projects.
• Strong analytical and problem-solving skills.
• Good communication skills and ability to work with both business and technical stakeholders.
• Curiosity and willingness to continuously learn new technologies.

Nice to Have

• Experience with Microsoft technologies, such as: Microsoft Copilot; Power Automate; Power Platform; SharePoint; Microsoft 365; Azure AI services.
• Basic understanding of APIs and integrations.
• Experience with low-code/no-code platforms.
• Basic knowledge of Python or scripting languages.
• Experience delivering internal automation or AI transformation initiatives.

What We Offer

• Opportunity to work on innovative AI projects with real business impact.
• Exposure to modern AI technologies and rapidly evolving tools.
• Freedom to experiment, learn, and help shape future AI solutions.
• Collaboration with a growing AI-focused team.
• Direct involvement in solution design, innovation, and project delivery.
• Continuous learning and professional development opportunities.

Policy statements:
www.pwc.com/ua/uk/about/privacy.html

We’re expanding our automation team—and we’re looking for someone who loves building AI agents, not just “plugging ChatGPT into everything.” If you’re interested in more than just writing prompts—if you want to create systems that make their own decisions, handle errors, and run in production without constant supervision—read on 👇

Who We Are

Our team automates routine business processes using AI agents: alerts, mailings, reminders, and other tasks that used to be handled manually. We currently have three specialists on the team, and we’re growing. We work on a wide range of projects—from small integrations between departments to large-scale initiatives with a real impact on the business.

What we expect from you during our collaboration: 

• Development and implementation of multi-agent systems
• Build and maintain custom integrations via APIs
• Set up and optimize data workflows: webhooks, JSON/XML parsing, Salesforce automation, Google Sheets, and Slack, TG notifications.
• Develop effective AI prompts to integrate large language models (LLMs) into business operations
• Development of Retrieval-Augmented Generation (RAG) models
• Monitor automation processes, resolve incidents promptly, and drive ongoing improvements
• Research of new tools, libraries and practices in the field of AI
  
   

This role is a great fit if you: 

• 1-3 years of experience with no-code/low-code automation, n8n as primary tool (Zapier/Make — a plus)
• Practical experience building at least one agent-based workflow (not a linear automation)
• Practical experience with REST APIs, OAuth2, webhooks
• Python or JavaScript — ability to write custom scripts/nodes for integrations
• Relational databases (SQL) — storing state, logs, scraping results
• Experience integrating at least one LLM provider (OpenAI/Claude/Ollama) into a production workflow
• Prompt engineering — writing and optimizing prompts
  
  The following would be a plus: 
• Experience with web scraping (Playwright, Scrapy, Selenium, or similar)
• Familiarity with agent frameworks (LangChain, LangGraph)
• Understanding of how queues and schedulers work (cron, SQS, or similar)
• Experience in the iGambling industry
• Basic knowledge of DevOps: CI/CD, monitoring
  
  What we offer:
• 24 days of vacation + days off
• Remote work — choose any corner of the world to “be with us”
• Support for your learning and professional development through external courses and educational activities (conferences, webinars, etc.)
• Benefit Café: reimbursement for sports activities, English language courses, and mental health support
• Health insurance
• Financial support during difficult life situations—we understand that this is an extremely challenging time for every Ukrainian, so we’re here for you not only on the “good days” but also on the “tough ones.”
• Employee referral program. The opportunity to directly influence business development and hiring strategy at a rapidly growing international company.

Hiring process: Recruiter interview → Interview with Hiring Manager → Reference check → Job Offer.

💌 It takes 7 days to review your resume.
If you haven’t heard back from a recruiter, it means your experience doesn’t currently match the requirements for this role—we’d be happy to stay in touch about other job openings!