Jobs ML / AI

Applefy, a leading mobile and web development agency, is seeking an AI Engineer to join our team on an ongoing project.

The project is an AI customer-support agent for an e-commerce company. You will build the agent that answers customers from the client's own knowledge base, looks up live order and account data, and hands off to human agents in Zendesk with full context. 

This suits an engineer who wants to ship production AI, not just prototypes, and who cares about accuracy and safety as much as speed.
 

What We Offer:

• Flexible work schedule: Manage your own time and work at your own pace.
• Fully remote: Work from anywhere in the world.
• Comprehensive leave policy: All official holidays, 20 days of paid vacation, and 10 sick days without needing a doctor's note. [confirm]
• Hands-on product work: You will work directly with the founder and the client team, with weekly syncs and a demo at the end of each milestone.
   

Key Requirements:

• 4+ years of backend engineering experience, with strong Python (FastAPI or similar)
• Hands-on experience building LLM features in production, including tool calling, prompt design and output evaluation
• Practical RAG experience: chunking, hybrid search, source citations, and knowing when a model should decline to answer
• Experience integrating with third-party REST APIs, including authentication, retries and error handling
• Automated testing discipline, with unit and integration coverage targets you can explain
• A working understanding of GDPR and of protecting personal data in logs and prompts 
• Strong communication and soft skills
• Proficiency in spoken and written English
• Keen attention to detail
• A desire to learn and grow professionally
   

Preferred Qualifications:

• Experience with the Zendesk or Notion APIs
• Experience with LLM tracing and evaluation tools such as Langfuse
• Experience with prompt-injection defence or red-teaming
• Experience with EU cloud hosting and PostgreSQL with pgvector
• A React background for an embeddable chat widget
   

How to apply: Send a short note on the most relevant agent or RAG system you have built, a link to code or a demo if possible, and your availability. 
 

We’re looking for an AI Research Scientist to join our AI&Research Unit, a team dedicated to pushing the boundaries of fundamental artificial intelligence and bridging the gap between academic advancements and real-world technology.

Our fundamental research stream focuses on on-device LLM efficiency, deep architectural explorations, and localized machine learning solutions for the macOS ecosystem. It helps uncover high-level utility and solve complex technical challenges directly on user hardware, establishing our technology as a generalized leader in the global market.

As an AI Research Scientist, you will take deep ownership of our fundamental research initiatives. You’ll define, test, and coordinate advanced optimization workflows and structural model modifications while driving strategic collaborations with global scientific entities.

If you’re excited to lay the foundation for on-device AI efficiency to become a global industry standard, we’d love to hear from you!

In this role, you will:

• Prepare fundamental research proposals within our specialized LLM efficiency and optimization streams.
• Investigate new directions in LLM optimization by surveying relevant academic publications, formulating hypotheses, and running deep-dive experiments.
• Collaborate closely with internal research scientists and external academic labs on joint research projects and scientific publications.
• Work alongside the applied research stream to surface, validate, and transition relevant research prototypes into downstream production environments.
• Contribute to a strong publication record at top-tier international AI conferences, 
• Take full ownership of your research niche, driving initiatives from ideation to implementation with a high degree of independence and autonomy.
• Take part in internal knowledge-sharing sessions and weekly paper clubs to consistently improve domain expertise.

Skills you’ll need to bring:

• Deep experience in Natural Language Processing (NLP) or a similar machine learning domain, gained through solid academic work, industry experience, or both.
• Strong theoretical and practical understanding of recent LLM optimization techniques (ex. quantization, KV-cache compression, speculative decoding, and distillation).
• Direct hands-on experience with parameter-efficient fine-tuning (including LoRA and other adapters) and mixture-of-experts (MoE) architectures.
• Advanced prototyping skills and a proven ability to implement complex algorithms and architectures directly from academic papers.
• Fluent programming capabilities in Python and modern frameworks such as PyTorch, JAX, or TensorFlow.
• Robust fundamental knowledge of linear algebra, probability theory, and mathematical statistics.
• Upper-intermediate level of English or higher for active scientific writing, international lab collaboration, and conference presentations.
• Native or near-native Ukrainian language proficiency.

As a plus:

• A track record of publishing original research at international research conferences in AI/ML/SE/HCI domains.
• Practical experience in performance engineering, including code profiling and low-level optimization (GPU, Metal, C++...).
• Hands-on experience training, running, or deploying localized LLM models on device frameworks like MLX.

• Our client is an energy solutions provider. Our AI-enabled platform supports operations, tracking and decision-making to optimize large-scale renewable and traditional energy portfolios. We're delivering a key client MVP in February 2027, and the project continues into 2028. Our stack: Ruby on Rails, Node.js/TypeScript and Python services, PostgreSQL, Snowflake and AWS. We're looking for an applied AI engineer to build AI with real, measurable benefit across our operations and products.

   

• Responsibilities:

  Work closely with product teams to help define and execute technical criteria
  Find high-value uses for AI and define how success is measured
  Design, build and ship LLM-powered features and agents from prototype to production, such as automating client data onboarding
  Own retrieval and RAG over our data, building on the foundation our data engineers prepare
  Build evals and monitoring that track quality, cost and latency, and improve systems based on the results
  Help refine our customer-facing AI features

   

• Mandatory Skills Description:

  Nearshore strongly preferred; otherwise at least 4 hours of daily overlap with US Pacific Time

  Mid-to-senior software engineer who has shipped LLM-based features or agents to production, not only prototypes
  Production experience in Python (preferred) or Node.js/TypeScript
  Building with LLMs: prompt and tool design, structured outputs, retrieval/RAG and agent orchestration
  Evaluating AI systems: eval sets built from representative data, automated graders, human review and production monitoring
  AWS or another enterprise cloud platform, including its AI services (AWS Bedrock preferred)
  AI-native development: daily use of agentic AI coding tools, and experience scaling shared AI workflows across a team and into the development lifecycle, including CI/CD
  Strong English and communication skills

   

• Nice-to-Have Skills Description:

  Agent tool protocols such as MCP
  SQL and cloud warehouse data (Snowflake preferred)
  Infrastructure as code (e.g. Terraform)
  Exposure to energy, utilities or sustainability data

   

• Languages:
  • English: B2 Upper Intermediate

Solid Software is looking for an AI Software Architect/ Senior AI Engineer to design and deliver production-grade solutions powered by LLMs. The role requires deep expertise in architecting, building, and operating complex AI systems: RAG, agentic workflows, tool calling, evaluation frameworks, and observability platforms.

The ideal candidate pairs strong software engineering fundamentals with a track record of shipping real-world AI products. Beyond experimentation, you can design scalable, reliable, and cost-effective LLM solutions that run successfully in production, with a solid grasp of modern AI architecture patterns, prompt engineering, retrieval systems, and agent orchestration.

What will you do?
 

• Own the architecture of AI-powered services and ensure their effective integration with backend, mobile, and web applications.
• Design, build, and maintain production-grade LLM applications using modern AI frameworks and orchestration platforms.
• Lead technical design reviews and drive architectural decisions across AI services, backend systems, data pipelines, and cloud infrastructure.
• Design and implement agentic workflows involving tool use, function calling, multi-agent systems, planning, memory management, and reasoning chains.
• Design and optimize RAG architectures using vector databases, embeddings, document processing pipelines, and retrieval optimization techniques.
• Establish evaluation frameworks to assess AI quality, reliability, latency, cost, and business impact, including benchmarking and automated quality assessment.
• Implement AI observability and monitoring using tools such as Langfuse, LangSmith, OpenTelemetry, and similar platforms.
• Optimize prompts, retrieval strategies, model selection, and system architecture to improve accuracy, performance, reliability, and cost efficiency.
• Design scalable APIs and services that expose AI capabilities to internal and external applications, and deploy them on cloud platforms, primarily Google Cloud Platform (GCP).
• Collaborate with software engineers, data scientists, product managers, and domain experts to translate business requirements into practical AI solutions.
• Define AI engineering standards, best practices, and governance processes to support the development and maintenance of reliable AI systems.
• Mentor engineers working on AI initiatives and contribute to architectural decisions and technical direction.
• Document AI architectures, workflows, evaluation methodologies, and operational procedures to ensure maintainability and knowledge sharing.

Requirements:
 

• 10+ years of software engineering experience, including 5+ years building LLM-based and generative AI solutions in production.
• Upper-Intermediate English (B2 or C1) for comfortable verbal communication within an international team.
• A Master's degree in Computer Science, Artificial Intelligence, Machine Learning, Software Engineering, or a related field.
• Strong Python development skills (3+ years) and solid software engineering fundamentals, including experience designing scalable APIs and cloud-native architectures.
• Hands-on experience with AI orchestration frameworks such as LangGraph, LangChain, LlamaIndex, CrewAI, or equivalent technologies.
• Practical experience designing and implementing agentic systems involving tool use, function calling, planning, memory management, and multi-agent workflows.
• Strong expertise in RAG architectures, vector databases, embeddings, prompting strategies, context management, and retrieval techniques.
• Experience with AI evaluation and observability tools such as Langfuse, LangSmith, or similar platforms, including benchmarking, monitoring, and automated quality assessment.
• Experience working with structured and unstructured data pipelines and databases, including PostgreSQL, vector databases, and document stores.
• Production deployment experience with Docker, Kubernetes, cloud platforms, and CI/CD pipelines.
• Ability to evaluate architectural trade-offs involving model performance, latency, reliability, maintainability, and cost.
• Strong communication, technical leadership, and mentoring skills, with the ability to collaborate effectively across engineering, data, and product teams.

Nice to have:

• Experience working with commercial and open-source models, including OpenAI, Anthropic, Gemini, Llama, and Mistral, as well as fine-tuning techniques.
• Experience in regulated, privacy-sensitive, or high-availability environments.
• Experience integrating AI capabilities into mobile and web applications.
• Familiarity with synthetic data generation and model optimization techniques.

Why Solid Software?

• We support Ukraine; 
• A wonderful team of enthusiasts and like-minded people;
• Atmosphere of comfortable work & life balance;
• Flexible schedule and work-from-home opportunity;
• Opportunity to work on projects with different directions (web, mobile, tablet, watch, desktop);
• MacBook Pro and great tech;
• Decent compensation;
• Lack of bureaucracy;
• Compensation for professional events, sports activities;
• Corporate online parties and fun team-buildings;
• Anniversary and birthday presents.

Professional growth:

• Onboarding and mentorship program with a dedicated onboarding guide built by our team;
• Internal Career Path program from Developer to Architect that consists of knowledge areas for IT specialists, books, training sessions, and work activities;
• Corporate library with the best programming books (+ an ability to order a particular book if we don't have it);
• Professional and constant feedback.

We truly value the unique talents and skills that each individual brings to our company. As we continue on our journey of growth, we eagerly anticipate the opportunity to welcome you into our team. 

Apply now and help us shape what comes next!

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.

PwC Digital team is a modern software house within a large consulting company. We combine start-up dynamics and innovation with the extensive opportunities of PwC’s global network.

Join us and seize the opportunity to work with cutting-edge technologies such as GenAI, AI agents & copilots, cloud computing, chatbots, data lakes, and advanced machine learning algorithms, all built on a foundation of modern application development across diverse frontend and backend technologies.

Your future role

As an AI Engineer (Python + GenAI), you will:

• Develop innovative solutions, both internally and for our PwC US clients, leveraging cutting-edge machine learning and AI technologies.
• Develop intelligent assistants using the latest Large Language Models (LLMs), such as GPT-4, Falcon 2, Llama 3, and Mixtral.
• Apply Retrieval-Augmented Generation (RAG) techniques and agent frameworks such as LangGraph and CrewAI.
• Use your AI and software engineering expertise to recommend effective technical approaches and solution architectures for addressing business challenges.
• Participate in software deployments and work closely with PwC industry experts and users to solve ongoing issues.
• Collect, preprocess, and analyze large datasets for training AI models.
• Contribute to project documentation.

Apply if you have:

• 3+ years of relevant professional experience.
• Professional experience building applications using Large Language Models (LLMs) and related concepts and design patterns, including RAG, vector databases, embeddings, prompt engineering, and multi-agent systems.
• Familiarity with LLM frameworks such as LangChain and LlamaIndex.
• Strong knowledge and experience in production-grade Python development.
• Understanding of cloud concepts and architectures, with hands-on experience using Azure/GCP/AWS.
• Experience with containerization tools such as Docker and Kubernetes.
• Expertise in data manipulation in Python using tools such as Pandas and NumPy.
• Proficiency in English, both written and spoken.
• Excellent analytical and problem-solving skills.

Nice to have:

• Knowledge of frameworks and Python libraries related to GenAI agents, such as LangGraph, CrewAI, AutoGen, and TaskWeaver.
• Knowledge of Natural Language Processing (NLP) techniques.
• Knowledge of an additional programming language, such as C#, Go, or Java.

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

We are looking for a Computer Vision Engineer to join our team and develop vision-based systems for UAV applications.
In this role, you will work on the development of computer vision algorithms and their deployment on resource-constrained devices. You will be involved across the development cycle, from algorithm development and hardware evaluation to testing, performance optimization, and deployment.
This is a product-facing role where you will work closely with stakeholders from multiple departments and teams to develop reliable vision-based solutions for real-world applications.
​
Responsibilities:

• Develop and optimize computer vision algorithms, focusing on tasks such as object detection, tracking, and navigation for real-time edge inference
• Implement and customize machine learning models and vision frameworks, ensuring seamless integration with existing drone systems and hardware
• Conduct extensive testing and validation of algorithms in real-world scenarios, fine-tuning parameters and optimizing performance for robust performance in various conditions
• Evaluate and provide input on appropriate camera sensors, lenses, and onboard computing hardware for vision applications
• Develop repeatable testing methods and build data pipelines to evaluate and continuously improve the performance of vision models

• Collaborate with computer vision and robotics experts to leverage the latest advancements in the field and integrate them into the systems

   

Requirements:

• Proven ability to develop high-performance, real-time applications in C++ or Rust, specifically leveraging ROS2 for distributed messaging and OpenCV for real-time image processing or feature detection
• Strong hands-on experience developing and implementing computer vision systems for real-world, real-time embedded applications
• Deep understanding of both traditional computer vision techniques (e.g., feature extraction, optical flow, camera calibration) and modern deep learning architectures (e.g., CNNs, Vision Transformers)
• Track record of having implemented and deployed vision applications on robotic platforms in real applications
• Strong analytical and problem-solving skills, with the ability to design and evaluate complex algorithms in real-world scenarios
• Effective communication skills and the ability to work collaboratively in multidisciplinary teams, interacting with researchers, engineers, and external stakeholders
• Ability to effectively navigate ambiguity and lead across in a fast-paced environment

• English at B2–C1 level for communication with international colleagues and working with technical documentation.

   

We Offer:

• Official employment under Ukrainian labor law
• Military booking
• Medical insurance
• Individual English lessons
• Stock Options
• Opportunity to work on cutting-edge UAV systems and grow professionally

About the Product

We are developing a platform of AI analyst coworkers that deliver industry insights. The agents operate in secure, sandboxed environments and can use tools, communicate across channels, and complete complex tasks with human oversight.

About the Role

You will join a small engineering team building and operating the platform’s agentic AI capabilities. This is a hands-on role covering AI agents, system architecture, production reliability, feature design and secure deployment.

Tech Stack

- TypeScript, Node.js, and Bun

- LLM APIs, agent SDKs, and MCP

- SQL and SQLite

- GCP, including Cloud Run, Cloud Build, and Artifact Registry

- Terraform and CI/CD

- Event-driven messaging and asynchronous processing

- Structured logging, monitoring, and tracing

Key Responsibilities

- Design and build production AI agents that can plan, use tools, maintain context, and complete complex tasks.

- Design scalable systems for agent orchestration, messaging, task execution, permissions, and persistent state.

- Integrate LLM providers, external APIs, databases, and communication channels.

- Build secure, sandboxed environments for executing agent workloads.

- Develop evaluation, monitoring, and debugging tools for agent quality and reliability.

- Deploy and operate AI services on GCP.

- Own technical decisions and establish strong engineering, testing, and security practices.

Required Skills

- 7+ years of software engineering experience.

- Hands-on experience delivering production AI or agentic systems used by real users.

- Strong system design experience, particularly with distributed and event-driven systems.

- Strong backend development skills in TypeScript, Python, Go, Java, Rust, or a similar language.

- Experience with LLM APIs, tool calling, structured outputs, context management, and agent workflows.

- Experience with SQL databases, asynchronous processing, retries, idempotency, and failure handling.

- Production experience with GCP, Docker, CI/CD, and infrastructure as code.

- Strong understanding of application security, permissions, secrets, and workload isolation.

- Experience with observability, incident investigation, and production operations.

- Ability to work independently and communicate clearly in a fast-moving environment.

Nice to Have

- Experience with agent frameworks such as LangGraph, LangChain, CrewAI, OpenAI Agents SDK, Claude Agent SDK, or similar.

- Experience with Terraform, Kubernetes, vector search, RAG, or multi-agent systems.

- Experience with financial research or analyst workflows.

Who We Are

Adélie Cognition builds solutions for a private investment firms and offices powered by latest AI models.

We are looking for a Technical Lead for generative AI. You will be the technical face towards an international client in a heavy-asset, maintenance-oriented industry, and you will design and lead the delivery of the solutions.

What you will do

• Lead technical discussions with the client’s innovation team, together with our Managing Director
• Translate operational problems in maintenance and logistics into concrete AI use cases
• Design the architecture of GenAI solutions: advanced RAG, AI agents, document and data processing
• Choose the right approach: custom development, Azure AI or Microsoft low-code (Copilot Studio, Power Platform)
• Lead a small team of engineers and take solutions to production
• Define how solutions are run, monitored and supported after go-live

• Scope and estimate work realistically, in phases

   

Must have

• 7+ years of software engineering, including at least 2 years building LLM-based solutions
• At least one GenAI solution in production with real users, not only a prototype
• Advanced RAG: hybrid search, reranking, chunking strategies, permissions, evaluation (e.g. RAGAS, Langfuse)
• AI agents and tool calling (e.g. LangGraph, Semantic Kernel or similar)
• Strong Python
• Experience with Azure OpenAI or Azure AI Foundry
• Integration with existing systems via APIs (ERP, SharePoint, M365, Entra ID)
• Experience leading engineers or acting as tech lead on a project
• Fluent English (C1+); comfortable presenting to senior client stakeholders

• Honest communication: you say “I don’t know” and ask questions when needed

   

Nice to have

• Fine-tuning (LoRA/QLoRA) or self-hosted open-source LLMs (vLLM, Ollama)
• Copilot Studio, Power Platform, Power Automate, AI Builder
• Angular / TypeScript
• Industrial or OT data: time series, sensor data
• Experience in maintenance, asset management, energy, logistics or supply chain

• Docker, Kubernetes, CI/CD, monitoring

   

   

What we offer

• A lead role on innovative GenAI use cases with an international industrial client
• Direct collaboration with the Managing Director, short decision paths

• Remote work, EU or nearshore

   

When a soldier is wounded, the first record of their care is often a note on a card, a radio call or a medic's memory. Much of it is lost at the first handover. Caslog replaces that with a small recorder that clips onto the casualty, listens to the care being given and turns it into a clinical record that follows the patient from point of injury to hospital. We build it together with combat medics in Ukraine.

We are two founders, Swiss and Ukrainian, both serving military officers, and we have closed our pre-seed round. We're looking for an all-round engineer who builds with agents better than we do, and who makes the whole team faster at it.

WHAT YOU'LL WORK ON

Whatever moves the product forward most, across the whole stack. At the start that is mostly the AI core:

• The speech and extraction pipeline: noisy field audio in, a structured clinical record out, which a human reviews and signs off.
• The improvement loop: every change measured against the last one before it ships, on what medics care about (missed events, wrong details, invented content).
• Backend, security and infrastructure: encryption, access control, a full audit trail, processing that survives crashes, deployments customers can run themselves.
• How we build with agents: the harness, context, review and tests that let a very small team ship what used to take a department.

Your first goal: get the pipeline ready for the device's field tests with Ukrainian medics, with an evaluation set agreed with medics and results that measurably improve against it. You work closely with our technical founder and shape the backlog together. Good arguments change the plan.

OUR STACK

Python, PostgreSQL, Docker and GitLab CI on Google Cloud. Model work in PyTorch, Hugging Face Transformers and NVIDIA NeMo where the product needs it. If you'd pick something better for a job, say so.

WHO YOU ARE

You are a top agentic development talent. You use Claude Code, Codex, OpenCode, Hermes or a similar harness every day, and you know it better than most people who build with it. You can show, for example, that you:

• run several agents in parallel on isolated branches or worktrees and merge their work without chaos;
• write the specs, tests and checks that let an agent verify its own work, and catch it when it says "done" without having run them;
• keep context lean and durable: project instruction files, skills, subagents, hooks, MCP tools and notes that survive between sessions;
• put limits around agents: sandboxes, least-privilege permissions, review gates, token and spend budgets;
• evaluate the agents themselves: compare models and prompts on your own tasks, find where they fail and fix that in the process, not only in the prompt;
• use agents beyond code: labelling data, generating synthetic data, triaging logs and incidents;
• leverage local models and keep up with recent developments such as Decisions APIs.

You have 5+ years of building and running production software, so you know what good code looks like and notice when an agent gets it wrong. Underneath, you're a real engineer:

• You have depth in backends, and you've fixed them when they broke in production.
• You treat data as carefully as code and think about security by default: clean test splits, authentication, secrets, least privilege.
• You are pedantic about cleaning up repos and keeping them tidy, simple and secure.
• You can design a system end to end and explain your choices in plain words.

Bonus: fine-tuning and serving models, audio and speech work, speaking Ukrainian, a background in medicine or the military.

FORMAT AND WHAT WE OFFER

• Full-time, part-time or contractor: we're open to the format that fits you. Pay and share options depend on the format and the time you commit, and we agree them.
• Work on the core of a product with an unusually clear purpose: wounded people getting the right care.
• We pay for your coding-agent subscriptions. Fully remote, with occasional meetups in Kyiv.

This is defense work. If that's not for you, we understand and would rather you know now. We don't hire citizens of Russia or Belarus, and every hire passes a background check.

HOW TO APPLY

No cover letter needed. Send us your CV, your GitHub and LinkedIn profiles, and something you built with agents. Tell us about one place where the agent got it wrong and how you noticed. If it's a match, we run a one-week paid trial on real work together.

GlobalLogic takes an opportunity to partner with a leading global threat intelligence platform to design and deliver an enterprise-scale, Human-in-the-Loop (HITL) AI agent platform. The initiative centers on accelerating expert analyst decision-making by augmenting high-complexity threat intelligence workflows with cutting-edge generative and agentic AI systems.

Requirements

Essential qualifications

• 5+ years of engineering, including 2+ years on production retrieval-augmented generation (RAG) or search systems.
• Embeddings, vector databases (Vertex AI Vector Search, pgvector or similar), hybrid search and rerankers.
• LLM evaluation methods and tooling (Ragas, DeepEval, custom judges, golden-set design).
• Strong Python, from prototype through to production code.

Desirable qualifications

• An information retrieval or NLP research background.
• Vertex AI Search, BigQuery, and in-context learning optimization (for example, DSPy).
• Structured report generation and citation grounding.

Job responsibilities

• Build hybrid retrieval over enterprise sources (vector and keyword search), with reranking and permission-aware filtering.
• Build the precedent store: index decision points with human decisions and rewards, and retrieve the right examples at runtime.
• Deliver report generation and explanation layers with source attribution.
• Build automated evaluation: golden datasets, LLM-as-judge, regression suites, and A/B tests of few-shot strategies.
• Apply the dynamic few-shot approach to the LLM stage of alert triage.

We are looking for an AI/ML Research Scientist to join our team!

Responsibilities

• Conduct cutting-edge research in applying machine learning techniques to chip design and optimization problems
• Develop and implement algorithms using graph neural networks, diffusion models, and other advanced ML architectures
• Collaborate with cross-functional teams including engineers and researchers
• Publish research findings in top-tier conferences and journals
• Prototype and validate new approaches using modern ML frameworks
• Contribute to open-source or commercial EDA tools

Minimum Qualifications

• PhD with 1+ years of research experience in Electrical Engineering, Computer Science, Information Systems, or STEM-related field
• 1+ years of experience with modern machine learning architectures including Transformers, Graph Neural Networks, and Diffusion models
• Strong coding skills in Python and C++
• Experience with machine learning frameworks like PyTorch
• At least 1 publication in top machine learning conferences (NeurIPS, ICML, ICLR, etc.)

Preferred Qualifications

• Experience with deep learning on graphs (general graphs, circuit graphs, molecular graphs, or trees)
• Familiarity with classical search and optimization techniques (Genetic Algorithms, Monte-Carlo Tree Search, Dijkstra's Algorithm, etc.)
• Experience with EDA tools, either commercial or open-source
• Publications in top-tier venues focusing on AI for chip design or AI for materials science

Location: Fully Remote
Project: Enterprise Conversational AI Platform Migration to AWS

Project Overview

We are looking for an experienced Conversational AI Expert to support the migration of an existing contact center environment from Genesys and Cognigy AI to Amazon Connect and Amazon Bedrock AgentCore.

The project focuses on building a scalable, enterprise-grade AI platform on AWS, with particular emphasis on Retrieval-Augmented Generation (RAG), enterprise knowledge integration, and multi-agent orchestration.

A key part of the solution is developing a comprehensive RAG-based knowledge layer that brings together large volumes of enterprise information, including documentation, repositories, internal services, and other knowledge sources. This knowledge must be made accessible to AI agents through appropriate retrieval mechanisms, APIs, gateways, and cloud-based integrations.

The role involves coordinating AI agents and sub-agents across AWS services and integration layers, ensuring reliable access to enterprise knowledge and backend systems. While the platform supports voice and chat channels, the primary focus of this position is on the underlying AI architecture, knowledge retrieval, and agent integration rather than voice technology or telephony implementation.

Key Responsibilities

• Design, implement, and optimize enterprise RAG solutions that enable AI agents to retrieve and use information from large, diverse knowledge sources.
• Integrate enterprise documentation, code repositories, internal services, and other data sources into AI-powered knowledge and retrieval pipelines.
• Configure and orchestrate AI agents and sub-agents using Amazon Bedrock AgentCore and Amazon Connect.
• Design and implement integrations between Amazon Connect AI agents and Amazon Bedrock AgentCore agents and runtime through the Bedrock AgentCore Gateway.
• Coordinate end-to-end interactions between AI agents, retrieval components, AWS services, gateways, APIs, and backend systems.
• Collaborate with the dedicated Bedrock AgentCore development team responsible for agent logic, aligning interfaces, input/output schemas, and error-handling strategies.
• Apply best practices for retrieval quality, prompt engineering, context management, agent guardrails, and reliable access to enterprise knowledge.
• Test, evaluate, and continuously improve the quality, relevance, and reliability of AI-generated responses and agent workflows.
• Document solution patterns, integration guidelines, and architectural decisions, and transfer knowledge to the client and project team.

Required Qualifications

• Several years of hands-on experience building or integrating conversational AI, LLM-based applications, or enterprise AI assistants.
• Practical experience with RAG architectures, including knowledge ingestion, document processing, retrieval pipelines, and grounding LLM responses in enterprise information.
• Experience integrating AI agents with multiple data sources, APIs, repositories, and enterprise backend systems.
• Experience with multi-agent systems, agent orchestration, or integrating LLM-powered components across distributed services.
• Experience with AWS Bedrock in enterprise integration scenarios, ideally including Amazon Bedrock AgentCore and the AgentCore Gateway, or comparable API and gateway technologies.
• Good understanding of AWS services for AI, serverless computing, and integration, such as AWS Lambda, API Gateway, EventBridge, and CloudWatch.
• Ability to work effectively across complex enterprise environments involving multiple teams, services, APIs, and integration layers.
• English proficiency at B1 level or higher, with the ability to communicate effectively in international project teams.

Preferred Qualifications

• Hands-on experience with Amazon Bedrock AgentCore, including agent runtime, gateway integrations, tool access, and orchestration patterns.
• Experience with Amazon Connect AI capabilities and integrations, including contact flows and connecting conversational interfaces to external AI services.
• Familiarity with LangChain and/or LangGraph for implementing RAG pipelines and orchestrating complex LLM or multi-agent workflows.
• Experience designing enterprise knowledge architectures that combine multiple repositories, document sources, internal services, and APIs.
• Experience with monitoring, evaluating, and improving RAG and agent-based systems in production environments.
• Experience with enterprise contact center migrations, particularly from Genesys and/or Cognigy AI to Amazon Connect.
• Fluent business English, including participation in technical workshops and coordination with international stakeholders.

Engagement Details

• Work arrangement: Fully remote
• Primary focus: Enterprise RAG, knowledge integration, multi-agent orchestration, and AWS-based AI integrations
• Technology stack: Amazon Bedrock AgentCore, Amazon Connect, AWS Lambda, API Gateway, EventBridge, CloudWatch, and related AWS services

We’re looking for a Middle/Senior AI/ML Engineer to join a data-driven digital product used by millions of users across the MENA region. You’ll build predictive and optimization models that improve pricing accuracy, lead scoring, and data quality, taking them from feature development and evaluation to AWS deployment and monitoring.
 

Required for this role

• 4+ years of experience in Data Science or Analytics roles, with a demonstrable track record of business impact.
• A bachelor’s degree or higher in Mathematics, Computer Science, Data Science, or another quantitative field.
• Strong knowledge of Python, including pandas, NumPy, and Scikit-learn, together with proficiency in SQL.
• Practical experience with PyTorch or TensorFlow.
• Hands-on experience with supervised and unsupervised learning, feature engineering, model tuning, and evaluation metrics.
• Experience deploying machine learning models using AWS SageMaker, AWS Lambda, and Amazon ECS.
• Solid understanding of statistical methods, experimental design, and hypothesis testing.
• Ability to translate ambiguous business problems into clear technical solutions and data-driven initiatives.
• Strong communication skills, including the ability to explain complex findings to non-technical stakeholders.
   

Your responsibilities

• Design and implement predictive and optimization models using classical machine learning, statistical modeling, and deep learning techniques.
• Develop models that improve pricing accuracy, lead scoring, and listing quality across the property portal.
• Own the full model lifecycle, from feature extraction and development to production deployment on AWS SageMaker, AWS Lambda, and Amazon ECS.
• Establish MLOps practices, including CI/CD pipelines for models and production monitoring.
• Build evaluation pipelines and support A/B testing frameworks to validate model performance and reliability.
• Collaborate with engineering teams to ensure production models meet latency, scalability, and operational requirements.
• Monitor model performance, data quality, and drift over time, and contribute to reliable monitoring practices.
• Partner with Product, Strategy, and Commercial teams to align project objectives and translate business goals into data-driven solutions.
   

What you get

Your time off

• 18 paid vacation days and 10 paid sick days annually
• 10 Ukrainian public holidays
• Maternity and paternity leaves
• Marriage and Parenthood Package
• Additional leave for major life events
• Sabbatical leave opportunities
   

Learning & growth

• Sombra University workshops and internal learning programs
• Tech Communities and knowledge sharing sessions
• Language courses and workshops
• Mentorship opportunities
   

Health & well-being

• Sports compensation or health insurance coverage
• Participation in races and marathons
• Corporate doctor (telemedicine)
• Well-being initiatives and workshops
   

And even more

• Company-provided technical equipment
• PE administration and tax support
• Internal referral program
• IT Club loyalty program
• Company events and volunteering initiatives
   

Before you apply

Our recruitment team will carefully review your profile, and if we see a good match with the role, we’ll reach out to you shortly.

If you don’t hear from us within 5 business days, it means we’ve decided to continue the process with other candidates for this position. Thanks for understanding.

We are an IT services company based in San Francisco, USA. We build and acquihire expert engineering and data science teams to help our clients meet their business needs and solve operational challenges.

About the role

We are looking for an experienced Senior AI Engineer to develop and scale an AI Agent platform that automates customer interactions across voice, SMS, and chat channels.

You will design, build, and maintain production AI systems that handle high volumes of real-time conversations, integrate with external services, and automate business workflows. The role requires strong software engineering expertise, hands-on experience with AI agents, and the ability to deliver reliable, scalable solutions.

This position requires working hours from 3:00 PM to 11:00 PM Kyiv time.

Key responsibilities

• Design, develop, and scale AI agent systems for real-time, multi-turn customer interactions.
• Build and maintain APIs, backend services, and infrastructure supporting AI-driven workflows across multiple communication channels.
• Integrate AI agents with external tools, APIs, and business systems.
• Optimize system performance, response accuracy, latency, and reliability.
• Implement monitoring, observability, and evaluation processes for production AI agents.
• Own the development lifecycle, including architecture, implementation, deployment, and maintenance.
• Collaborate with engineering, product, and AI/ML teams to deliver and improve AI-powered features.

Required qualifications

• Minimum 8 years of professional software engineering experience.
• Strong programming skills in Go, Python, or Elixir.
• At least 1 year of hands-on experience deploying and maintaining AI agents in production environments.
• Experience building AI agents that interact with external tools, APIs, and automated workflows.
• Proven experience designing and maintaining distributed, high-throughput systems.
• Strong knowledge of backend development, API design, and production infrastructure.
• Experience with system monitoring, performance optimization, and troubleshooting.
• Strong problem-solving skills and ability to work independently in a fast-paced environment.
• English: Upper-Intermediate (B2) or higher, with strong communication skills.

Preferred

• Experience designing and implementing LLM evaluations, including accuracy, safety, reliability, and cost monitoring.
• Knowledge of prompt engineering, context management, and guardrail strategies.
• Experience with agent frameworks such as LangGraph, CrewAI, or AutoGen.
• Understanding of agent orchestration, memory management, and multi-step workflows.
• Experience with LLM fine-tuning and data curation.

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