Jobs ML / AI Engineer

We are hiring an AI Automation Specialist for a high-volume, automation-first publishing operation (stealth client). This is a hands-on builder role: design and maintain systems that remove manual work, reduce errors, and speed up execution.

Tech stack focus

• Python automation + data processing
• API integrations (REST, webhooks, CSV pipelines)
• n8n / Zapier (or similar)
• LLMs in real production workflows, prompt engineering
• Google Sheets/Excel (advanced), SQL, BigQuery (or similar)

Responsibilities

• Build AI-driven workflows for content, QA, analytics, and operations
• Automate repetitive high-volume processes via scripts + integrations
• Data ingestion/transformation/validation + monitoring/anomaly alerts
• Automated QA for links/UTMs/formatting/content structure
• Document systems so they can be scaled and maintained

Requirements

• 4+ years in automation / tech ops / data engineering (or similar)
• Systems-thinking, high ownership, strong execution discipline
• English: C1+

We are seeking a highly skilled Senior AI Engineer to design, integrate, and optimize AI-driven solutions across our platform. This role will focus on integrating existing AI tools and services, enhancing data processing and analysis workflows with AI, and laying the technical foundation for advanced AI capabilities.

You will work closely with backend, frontend, and product teams, and over time, grow into an AI Lead position, shaping the long-term AI strategy and architecture.

Key Responsibilities

AI Integration & Architecture

• Integrate and orchestrate third-party and in-house AI/ML tools (e.g., LLMs, embeddings, vector databases, AI APIs).
• Design scalable AI-powered services that integrate seamlessly with existing systems.
• Evaluate new AI technologies and tools, and recommend adoption based on business impact.

Data Processing & AI Optimization

• Optimize data pipelines for AI-driven processing, analysis, and automation.
• Apply AI techniques to improve data quality, insights generation, and operational efficiency.
• Collaborate with data and product teams to translate business needs into AI solutions.

Backend & Frontend Collaboration

• Build and maintain AI-enabled backend services using Python, AWS, and RESTful APIs.
• Expose AI capabilities via well-structured APIs for frontend consumption.
• Work with frontend engineers to integrate AI features into React applications.

Scalability, Reliability & Security

• Ensure AI solutions are production-ready, scalable, cost-efficient, and secure.
• Monitor performance, latency, and accuracy of AI systems in production.
• Implement best practices for model versioning, observability, and responsible AI use.

Leadership & Growth

• Act as a technical mentor for engineers working with AI-related features.
• Contribute to defining AI standards, best practices, and long-term roadmap.
• Gradually take ownership of AI architecture and strategy, growing into an AI Lead role.

Required Qualifications

• 5+ years of relevant experience in software engineering, machine learning, or AI-focused roles.
• Strong proficiency in Python, with experience building production backend systems.
• Hands-on experience with AI/ML integration, including LLMs, ML APIs, or AI platforms.
• Experience with AWS (e.g., EC2, Lambda, S3, SageMaker, or similar services).
• Solid understanding of RESTful API design and microservice architectures.
• Experience collaborating with frontend teams using React or similar frameworks.
• Strong knowledge of data processing, analysis pipelines, and performance optimization.
• Ability to design systems that balance experimentation with production reliability.

Nice to Have

• Experience with MLOps, model deployment, and monitoring.
• Familiarity with vector databases, retrieval-augmented generation (RAG), or agent-based systems.
• Experience optimizing AI cost, latency, and inference performance.
• Prior experience mentoring engineers or leading technical initiatives.
• Exposure to AI ethics, governance, and compliance considerations.

What We Offer

• Opportunity to build and scale AI capabilities in a real-world production environment.
• Clear growth path toward an AI Lead position with strategic ownership.
• High level of autonomy and technical influence.
• Collaborative environment working across backend, frontend, and product teams.
• Competitive compensation and benefits, commensurate with experience.

We are looking for an AI/ML Engineer (LLM and Autonomous Systems Specialist) to help us deliver an ambitious new project - the development and training of intelligent behavioral models for autonomous platforms capable of operating and making decisions without constant network connectivity.

The project lies at the intersection of artificial intelligence, machine learning, simulation, and robotics.

Its goal is to create a system where AI not only reacts but also understands context and adapts to its environment.

We are a technology-driven FinTech company that has gone far beyond traditional financial services - actively expanding R&D directions related to autonomous systems, model training, and next-generation agent architectures.

If you’re ready to build technologies at the intersection of AI, machine learning, and autonomous systems - welcome to the team!

Responsibilities:

• Train AI models that analyze sensor data and make autonomous decisions (Behavioral Cloning, Reinforcement Learning).
• Work with virtual simulation environments that create scenarios for reinforcement learning.
• Configure and optimize algorithms for computer vision and navigation — obstacle detection, route planning, spatial orientation.
• Transfer trained models from simulation to real devices and adapt them to limited hardware resources.
• Develop and test behavioral strategies for operation under weak or no connectivity.

Requirements:

• Strong experience with Python, PyTorch, and/or TensorFlow.
• Deep understanding of CNNs, RNNs, Transformers, and LLM fine-tuning techniques (LoRA, PEFT).
• Experience with LLM serving frameworks such as vLLM, Ollama.
• Simulation & Training: The AI model is initially trained in a virtual environment using cloud platforms.
• Computing Power: A separate high-performance computer.

Nice to have: 
 

• Work with simulation environments (AirSim, CARLA, Isaac Sim) for synthetic data generation and model validation.
• Data Handling: MongoDB is used as a local onboard database to store instructions and sensor data. 
• Hardware Integration: A Raspberry Pi acts as the intermediary, receiving AI commands and relaying them to the controller (e.g., Jetson, Pixhawk). 

What We Offer: 

• Competitive salary and performance-based bonuses.
• Opportunity to work on cutting-edge AI + blockchain projects.
• Flexible working hours and remote work options.
• Professional development, training, and access to AI & blockchain research resources.
• A collaborative and innovative work environment. 

Join us and help shape the future of AI-driven blockchain automation!

On behalf of our Client from Bulgaria, Mobilunity is looking for an AI Engineer.

Our Client is a leading software development company. The team excels in web and mobile software development, video streaming, defense, machine learning, automotive, e-commerce, and AI. 
They leverage top-tier technologies and expertise driven by a passion for innovation to drive progress.

Requirements:

• Extensive experience in AI/ML, deep learning, and cloud-based AI services (AWS, Azure, or Google Cloud).
• Proficiency in AI/ML frameworks such as TensorFlow, PyTorch, Scikit-learn, Langchain,and Hugging Face.
• Strong programming skills in Python or similar.
• Excellent proficiency with traditional SQL and big data technologies such as Apache, Spark, Hadoop, and distributed computing frameworks.
• Ability to analyze large datasets and derive business insights using BI tools like Tableau, Power BI, or similar.
• Experience with MLOps practices, including model deployment, monitoring, and CI/CD for AI workflows.

• Hands-on experience with APIs, microservices, and AI-driven automation solutions.

  
  Responsibilities:

• Design and implement cutting-edge AI-driven solutions leveraging the full spectrum of approaches from traditional ML learning to using LLMs.
• Work closely with data scientists, ML engineers, and software developers to ensure the successful deployment of AI models and applications.
• Stay updated on emerging AI technologies and industry best practices to provide innovative and forward-thinking recommendations to clients.
• Provide technical guidance on AI model lifecycle management, including training, tuning, monitoring, and optimization.
• Ensure AI solutions are scalable, secure, and compliant with industry regulations and best practices.
• Act as a trusted advisor to clients, helping them navigate AI adoption challenges and maximizing the impact of AI in their operations.
• Develop technical documentation, including solution architectures, white-papers , and best practice guides.
  
  Competencies:
• Experience in digital transformation, business process optimization, or AI strategy consulting.
• Knowledge of AI ethics, bias mitigation, and regulatory compliance in AI adoption.
• Excellent communication and presentation skills, capable of articulating complex AI concepts to non-technical stakeholders.
• Strong problem-solving and analytical skills, with the ability to design tailored AI solutions for diverse business challenges.
• Excellent familiarity with the SDLC and project management methodologies and tools (e.g. Jira, Confluence, etc.)
• Passion for innovation and continuous learning in the field of AI and emerging technologies.
• Ability to handle multiple client engagements and prioritize tasks in a fast-paced environment.

In return we offer

• The friendliest community of like-minded IT-people.
• Open knowledge-sharing environment – exclusive access to a rich pool of colleagues willing to share their endless insights into the broadest variety of modern technologies.
• Mobilunity Medical Insurance program designed to attend our teams’ needs.
• Paid vacations and sick leaves, including 5 paid days per year that don’t require a sick note.
• Perfect office location in the city-center (900m from Lukyanivska metro station with a green and spacious neighborhood) or remote mode engagement: you can choose a convenient one for you, with a possibility to fit together both.
• No open-spaces setup – separate rooms for every team’s comfort and multiple lounge and gaming zones.
• English classes in 1-to-1 & group modes with elements of gamification.
• Neverending fun: sports events, tournaments, music band, multiple affinity groups.

Come on board, and let's grow together!

We are an international developer of IT products for medicine and related services. Our products are used by more than 5,000 doctors and more than 1,000 clinics in Europe.

The goal is to attract the largest possible audience to the main projects - clinics and doctors up to 3 million. As well as expanding unique traffic to 10 million per day until 2025. We are looking for AI Engineer / AI Architect with deep knowledge of Fundamental Mathematics, Probability Theory and Bayesian Statistics, Graph Algorithms, Mathematics of Transformers, Hybrid AI Approaches, Uncertainty Assessment.

Must-have skills are:
1. ML and Data Science (Core):
- Expert in NLP & LLM: Deep understanding of Transformers architecture (BERT, RoBERTa, GPT, T5, Llama/Mistral). Experience with Large Language Models (LLM) – not prompt engineering, but fine-tuning (PEFT, LoRA) of open-source models on specific datasets.
- RAG (Retrieval-Augmented Generation): Experience building RAG systems is required. The AI ​​must be able to search for information in different data sources.
- Named Entity Recognition (NER) & Information Extraction: Ability to extract specific entities from unstructured text.
- Tabular Data & Classic ML: Confident use of classical algorithms (XGBoost, CatBoost, LightGBM) for analyzing structured data and building probability scoring models.
- Frameworks: PyTorch (preferred) or TensorFlow/Keras. Proficiency in HuggingFace, Scikit-learn, Pandas, and NumPy.

2. MLOps:
- Experience wrapping models in APIs (FastAPI, Flask) with minimal latency. 

- Docker knowledge and experience working with local GPU instances are required.
- Experience working with vector databases (Pinecone, Milvus, Qdrant, ChromaDB) for quickly searching for similar cases or working with knowledge bases.

- ML Pipelines: Experience building model training and retraining pipelines (Airflow, MLflow, DVC).

3. MedTech and Security:
- Practical working experience with sensitive personal data and GDPR/DSGVO requirements.

- It is important to be able to deploy and optimize local models (Llama 3, Mistral, Mixtral) within a closed company environment to ensure data privacy.
- Skills in quantization and distillation of models to speed up work without significant loss of quality.

Nice-to-have skills:
- Experience working specifically with medical data (EHR, EMR; HL7, FHIR, ICD-10/11 standards). 

- Knowledge of Interpretability/Explainable AI (XAI) methods. The end user should understand why the AI ​​suggested a particular option (SHAP, LIME).

- Experience with multimodal models.

What we offer:
- Paid holiday for 28 working days.
- Transparent incentive system.

Working with us means:
- Unique technological and innovative projects.
- Gaining experience in modern western world practices in security, scalable architecture, etc.
- In-depth knowledge of telemedicine.
- Working with Big data, high load, distributed computing and data buses.
- Socially important projects.
- Opportunity to influence both technology and product solutions.
- Profitability and stability of a large European company.

We are looking for an AI Developer for our company. For this position, we are considering only Ukrainians, from Ukraine or abroad.

Requirements:
- English is a must 
- back-end Python skills (Python, Django/FastAPI/Flask)
- AI & ML skills (prompt engineering, computer vision, voice recognition, etc.)

We value responsible and serious developers open to new knowledge and technologies.
The first stage is a meeting with HR, the second is a test task, and the last one is a technical interview. 

Job Description

We are hiring a Senior LLM Systems / Agent Infrastructure Engineer to optimize and scale a production multi-agent LLM system that translates natural language into Cypher / SQL queries, executes guarded graph retrieval, and synthesizes structured RAG responses. You will engineer a faster, cheaper, and more reliable LLM system in production.

What We’re Building

A production multi-agent LLM system that:

• Converts Natural Language (NL) → Cypher (Neo4j) / SQL (PostgreSQL)
• Executes guarded graph queries
• Runs structured Retrieval-Augmented Generation (RAG)
• Orchestrates used tools

What You’ll Own

• Cut NL → Cypher / SQL latency
• Optimize model routing & tool orchestration
• Replace unnecessary LLM calls with deterministic logic
• Redesign context strategy
• Evaluate / replace current LLM stack (Google ADK)

Outcome: A faster, cheaper, and more stable pipeline.

Required

• 5+ years backend / ML systems experience
• 2+ years production LLM pipelines experience
• Strong Python (async, FastAPI)
• Experience with agent frameworks (LangGraph, DSPy, Semantic Kernel, etc.)
• Structured outputs / function calling
• RAG over structured data
• LLM + SQL or graph DB integration
• Strong grasp of token economics & latency optimization
• Inference optimization (vLLM, batching, streaming)

We seek an AI Engineer with strong expertise in state-of-the-art techniques for RAG, LLM Agents. You will be responsible for designing, developing, and deploying AI-driven solutions for our Clients and in-house solutions. The ideal candidate has hands-on experience with a wide range of techniques in modern Agents development.

🧙‍♂️ In This Role You Will

• Develop AI agents, including chat agents and metric extraction agents.
• Create evaluation pipelines for agents, including tool usage and RAG (Retrieval-Augmented Generation) assessments like coherence and relevance.
• Improve results from Qdrant & Azure AI Search.
• Research and apply state-of-the-art techniques for agents and RAG systems.
• Maintain and support evaluation datasets.
• Write documentation for back-end integration or handle integration directly when needed.
   

🎯 You May Be Interested If

• You are excited about learning and working with AI technologies.
• You enjoy solving complex problems and have strong analytical skills.
• You thrive in a remote work setup and appreciate flexible working hours.
• You are eager to join a small, dynamic team and make a big impact.
• You value a company culture that promotes transparency, respect, and continuous learning.
• You are self-motivated and willing to learn new skills.
• Active code agents user.
   

🍰 Role Requirements

Agents

• Experience in LLM Agents architecture (not only Langchain)
• Qdrant (Must have), Azure AI Search, BM25 experience
• Semantic Reranking
• RAG evals (embeddings, LLM as a Judge)
• RAG (Naive, Graph, Hybrid, Agentic)
• Experience in different data mining techniques from unstructured data
• OCR
• PydanticAI

Web

• Django (DRF)
• Fastapi
• Celery

Infrastructure

• Azure Cloud
• Docker
   

💻 Working Conditions

• This is a fully remote position with the entire team across Ukraine.
• The team collaboratively defines deadlines, ensuring a balanced and manageable workload. The focus is on delivering commitments on time.
• 20 working days of paid vacation per year.
• Financial compensation for completing certifications and encouraging continuous learning and professional development.
• Preferred working hours: To ensure effective collaboration with our US-based client, the workday is shifted to the afternoon/evening. The 8-hour workday is scheduled within the 12:00 – 23:00 (Kyiv time) window, with the specific shift to be coordinated based on the required overlap

We are a British—Ukrainian air defence tech company building distributed systems across the frontline. We are looking for a Founding Engineer with deep expertise in Machine Learning and Computer Vision to take full ownership of the architecture and implementation of detection systems for our current and future product lines.

Our core value is impact for Ukraine: we build technology that makes a real difference on the actual battlefield, not in labs or on paper specs. We operate with a deep-tech mindset, pushing new technologies where engineering rigor truly matters. We value ownership and responsibility—people who execute, deliver, and stand behind the results.

We especially value engineers with strong analytical thinking and proven problem-solving skills — such as participation in mathematical/programming olympiads or experience contributing to open-source projects.

Key Responsibilities

• Detection Systems Development: Build and maintain the full lifecycle of ML solutions across the company’s product lines.
• Inference Engineering: Optimize models for real-time operations.
• Backlog Execution & Implementation:
  • Develop RF Classification models (Radio Frequency signals).
  • Improve the accuracy of DoA (Direction of Arrival) algorithms.
  • Implement drone behavior analysis and pilot localization algorithms.
• Best Practices: Define the architecture, tooling, and approaches to build a scalable ML infrastructure from the ground up.

Skills & Requirements

• Strong theoretical background in Linear Algebra, Probability, and Statistics.
• Experience with Computer Vision models: Classification, Object Recognition, and Tracking.
• Python + relevant ML libraries, PyTorch.
• Experience taking models to production (Production ML).
• Hands-on experience with inference engines.
• Ability to build low-latency, real-time detection pipelines.
• Proficiency in C++ and/or CUDA for building high-performance modules.

Nice to Have

• Experience in DefenseTech, SigInt (Signals Intelligence), or Embedded Systems.
• Understanding of Radio Frequency (RF) physics.

We Offer

• Meaningful and high-impact work in the AIR defense domain
• Practical R&D environment with real autonomy
• Direct influence on technical decisions and the product direction
• Work in an experienced senior engineering team
• Сlear, fast, senior-to-senior communication with a minimum number of team meetings
• Office in the center of Kyiv (available for onsite work when required)
• Full-time position
• Standard business hours; some tasks may require involvement outside the usual schedule (testing, critical updates)

US Company is searching for a couple of Senior AI Engineers into a complex, enterprise-level project for building sophisticated Agentic Systems, Adaptive RAG engines, capable of autonomous research to solve complex, real-world problems. Interesting project with cutting edge technologies, distributed team, full-time, an official contract. Remote work, flexible schedule.

Brief project description:

• The product is SaaS, which allows multiple functions for sustainability & operational risk management. The project is dedicated for developing of AI Center of Excellence.

Key areas of responsibility:

• Platform Engineering: Build and enhance scalable, reusable AI services (e.g., "Adaptive RAG Engine," "Text-to-SQL Service," and "Agentic Runtime") that product teams can easily integrate.
• Technical Contribution: Collaborate with principal engineers and architects. Participate in code reviews, write robust tests, and help drive the adoption of engineering best practices (CI/CD for AI, evaluation).
• Agentic Innovation: Develop and implement multi-agent systems capable of complex reasoning, planning, tool use, and self-correction (using frameworks like LangGraph or PydanticAI or Databrics' Agent Brics).
• Data Engineering: Load datasets and knowledge sources from external systems. Shape and transform data to optimize it for Hybrid or Semantic Search, providing the best possible knowledge context to LLMs.
• Production Readiness: Help move prototypes to production with a focus on latency, cost optimization, and reliability. Implement robust evaluation pipelines (LLM-as-a-Judge) to measure quality and prevent regression.
• Collaboration & Enablement: Partner with product teams to implement their AI roadmaps. Translate business requirements into concrete technical implementations.

Required skills (at least one or more for each category):

• Professional Experience: At least 5 years of professional experience in software development or Data Science.
• Education: Bachelor's or Master's degree in Computer Science, Mathematics, Engineering, Physics, or a related natural science field.
• Python Expertise: At least 5 years of hands-on experience with Python, writing clean, maintainable, and production-ready code.
• Strong Software Engineering Foundation: distributed systems, API design (FastAPI), and cloud architecture.
• Data Engineering Expertise: Data Engineering and Big Data (DeltaLake, Databrics etc.) experience are a big plus.
• GenAI Engineering Experience: Hands-on experience building production RAG systems. Chunking strategies, hybrid search (dense + sparse), re-ranking, and context management.
• Agentic Workflow Experience: You have experience building systems where LLMs use tools, maintain state, and execute multi-step plans. You are familiar with the challenges of loops, recursion, and hallucination mitigation.

Tech Stack:

• Languages: Python, TypeScript
• AI Frameworks: LangChain/LangGraph, Pydantic AI, MosaicAI
• Models: Azure OpenAI (GPT-4o, o1), Open Source LLMs (Llama 3, Mistral)
• Infrastructure: Azure AI Search, Azure Container Apps, Delta Lake, Vector Databases like Databrics Vector Search.

Work conditions:

• Distributed team, remote work.
• Kanban or scrum approach, 5-6 team members / team.
• Full-time (40 hours per week).
• Official contract: salary, sick-leave days, holidays, vacations.

Hiring process:

• Step 1 - preliminary interview (main questions) - 20 mins
• Step 2 - internal tech interview (tech questions) - 40-50 mins
• Step 3 - tech interview with team leader and architect - 1 hour

Requirements:

• Experience with Transformer models: BERT, RoBERTa, GPT, T5, LLaMA, Mistral, Falcon, etc.
• Strong knowledge of Python; experience with PyTorch, TensorFlow, and Hugging Face Transformers.
• Understanding of modern LLM architectures and fine-tuning techniques: LoRA, PEFT, Instruction Tuning, RAG.
• Experience with NLP tasks: classification, text generation, machine translation, QA systems, etc.
• Familiarity with evaluation metrics: accuracy, F1, BLEU, perplexity, ROUGE, etc.
• Basic knowledge of statistics and classical machine learning.
• Experience with MLflow, DVC, or similar tools.
• Experience with model containerization (Docker).
• Understanding of CI/CD principles in ML projects.
• Skills in model deployment using FastAPI / Flask / TorchServe / Triton.
• Experience with cloud infrastructure (AWS, GCP, Azure, or local cloud providers).

• Bonus: experience with Kubernetes, Airflow, Kubeflow, Ray.

   

Responsibilities:

• Selecting and configuring modern Transformer/LLM models for company-specific tasks.

Fine-tuning, LoRA tuning, model distillation, and quantization.

• Preparing and processing datasets (including augmentation).
• Deploying models to production and automating pipelines (data → training → inference).
• Monitoring model performance in production, retraining, and optimization.
• Collaborating with Data Engineers and DevOps to build the MLOps infrastructure.

• Evaluating model performance using various metrics and analyzing results to identify areas for improvement and optimization.

   

We offer you:

• Having the capability to create something new and witness your own input.
• You can find confidence in the future here, but rest assured it won't be dull. 
• Join a dynamic and expanding community. Our company is experiencing growth and expanding into Europe. Currently, we have offices in Kyiv, and Warsaw and plan to open additional locations in other countries. 
• Full-time employment contract.
• Multisport (light). 
• Paid vacation, sick leave.

Interested in joining our team? We invite you to submit your CV.

<By submitting your CV to LLC “GigaCloud”, EDRPOU code [39792589] (hereinafter referred to as the “Company”), in response to our vacancy, you consent to the processing of your personal data contained in the CV by the Company in accordance with the Law of Ukraine “On Personal Data Protection”, ISO 27701 Information Privacy Management System, and the provisions of the GDPR>.

We have existing N8N system that goes to Google and fetches business listings. We need to make modifications to that system

We also would like to build system that can connect to our Ticketing system (we are in technical support) analyze weekly tickets, write weekly blog, run it so google does not recognize that this is AI, then post this to Google profile and LinkedIn on regular basis. 

We have couple of other needs once this AI is integrated with Ticketing. 

Ideally we would like to find a person that is familiar with N8N or and Copilot and also is familiar with integrating those technologies with company needs such as marketing, automation, maybe AI voice answering service via Twilio. We then would like to offer AI solutions to our customers. 

We are helping to find an AI Automation Engineer for our client (startup — A performance marketing and traffic arbitrage team focused on scaling marketing campaigns using AI automation).

For this role, we’re looking for someone with 3+ years of continuous experience with AI products (e.g., AI agents) that have been released to production.

The company is creating an AI product and you can take part in its development.
 

Key Responsibilities:
 

• Develop and maintain AI agents capable of task execution (not just RAG/chatbots).
• Scale AI solutions from initial R&D to a stable production environment.
• Integrate LLMs (GPT, Gemini) with external tools like Jira, Slack, and advertising APIs.
• Optimize agent decision-making logic and error handling for live use.
  
  Technical Requirements:
   
  • 3+ years of professional experience in AI, ML, or Data Science.
  • Production experience: You must have released at least one AI agent-based system to production (real-world users/use cases).
  • Strong Python skills: Deep understanding of the Python ecosystem as the primary language for AI.
  • LLM & Agent Frameworks: Hands-on experience with LangChain, CrewAI, or similar, focusing on tool-calling and planning.
  • Engineering Basics: Solid experience with Docker, CI/CD, and cloud infrastructure (AWS) to ensure system reliability.
    
    Preferred Qualifications:
     
    • Experience with marketing or traffic arbitrage data.
    • Familiarity with Google Ads or Meta Ads APIs.
    • Basic knowledge of React (to better coordinate with frontend tasks).
      
      Location: Remote Ukraine, Hybrid (Warsaw) | Full-time
      Contract Duration: Long-term

IT Craft invites an AI Python Developer to join the company.

Requirements:

• Core Software Engineering: 3 + years Python 3.x; strong proficiency with FastAPI/Django, LangChain/LangGraph; Git, CI/CD, Docker.
• Generative AI & LLMs: Practical knowledge of leading models (GPT, Claude, Gemini, Mistral, Llama, Qwen, etc); working with them via public APIs, self-hosting, or managed platforms (AWS Bedrock, Azure OpenAI, GCP Vertex).
• LLM Techniques: Retrieval-Augmented Generation (RAG), Supervised Fine-Tuning (SFT), Parameter-Efficient Fine-Tuning (LoRA/QLoRA/PEFT), Reinforcement Learning from Human Feedback (RLHF), prompt engineering, and evaluation.
• Chatbots & Agents: Designing multi-turn conversational flows, tool invocation, agent routing/orchestration with LangChain, LangGraph, LlamaIndex, or similar.
• Vector Databases: Experience with FAISS, Milvus /Chroma / Pinecone / pgvector / S3 vector (indexing, similarity search, hybrid search).
• MCP Servers: Building and integrating Model Context Protocol (MCP) servers to securely expose domain tools/functions to LLMs.
• Automation Platforms:Advanced use of no-/low-code tools: n8n, Make (Integromat), Zapier (triggers, webhooks, custom modules).
• Soft Skills: Ownership mindset, rapid prototyping, clear technical writing; English at Upper-Intermediate (B2) or higher.

Key Responsibilities:

• Design & build end-to-end LLM workflows in Python — from data ingestion to inference APIs;
• Implement RAG pipelines: document parsing, embedding generation, vector search, and evaluation;
• Create chatbots / autonomous agents with frameworks such as LangChain, LangGraph, LlamaIndex, Semantic Kernel, or CrewAI;
• Expose tools via MCP servers so that external LLMs can invoke domain-specific actions;
• Integrate no-/low-code automation (n8n, Make, Zapier) to orchestrate business workflows;

• Write clean, test-driven code; set up CI/CD; monitor, log, and continuously improve model performance and system reliability.

   

Nice to Have:

• Experience with data privacy & compliance (GDPR, SOC 2);
• Operate in cloud & on-prem (Docker, GPU instances, AWS Bedrock/Azure OpenAI, self-hosted LLMs, etc.);
• Hands-on experience with TensorFlow, PyTorch, NumPy, Pandas; ability to train, fine-tune, and evaluate ML/LLM models.
• Familiarity with front-end stacks (React/Next.js, TypeScript) for building AI-powered user interfaces;
• Bonus: Experience in Generative Graphics, including Stable Diffusion, Inpainting techniques, and ControlNets;
• Bonus: Experience in LLM hosting and working with llama.cpp.

IT Craft offers:

• Competitive compensation according to the qualifications.
• Flexible working hours, remote work;
• Opportunity for career growth;
• Reward for sport activities;
• In-house English training;
• A friendly team of open-minded people.

Please send your CV!

By submitting your application, you consent to the processing of your personal data in accordance with IT Craft's Privacy Policy, available at https://itechcraft.com/datenschutz/.

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.

We are seeking an AI Architect to design, build, and guide the secure and scalable adoption of AI platforms and AI‑driven applications. This role partners with engineering, data science, and product teams to define AI solution architectures, ensure technical excellence, and embed best practices throughout the AI lifecycle—from data ingestion and model development to deployment and monitoring.

Key Responsibilities:

AI Architecture & Design

• Architect scalable AI/ML and LLM‑based solutions, including data flows, integration patterns, and deployment approaches.
• Conduct architectural reviews for new AI features and system changes.
• Define reference architectures and reusable AI patterns.

Collaboration With Engineering & Product Teams

• Partner with engineering, MLOps, and product teams to translate needs into AI solutions.
• Provide technical guidance that balances performance, cost, and speed.
• Build repeatable processes for reviewing AI capabilities and changes.

MLOps & Deployment

• Support integration of AI workflows into CI/CD processes.
• Promote automated testing, validation, and monitoring of AI models.
• Collaborate on tooling for model deployment, versioning, and observability.

Governance & Responsible AI

• Ensure AI designs follow internal governance and responsible AI principles.
• Support documentation and transparency for AI system behaviors.
• Align architectures with regulatory and compliance requirements.

Monitoring & Continuous Improvement

• Guide teams on monitoring, anomaly detection, and model performance tracking.
• Identify improvement opportunities and evolve AI architecture standards.
• Share best practices and mentor teams on modern AI technologies.

Required Skills:

• Experience in AI/ML system design, cloud‑native architecture, or application architecture.
• Strong understanding of the AI/ML development lifecycle, including training, deployment, and inference.
• Hands‑on exposure to LLM applications, RAG pipelines, vector databases, and API‑based AI integrations.
• Familiarity with MLOps, DevOps, and modern cloud platforms (Azure, AWS, GCP).
• Strong communication skills and ability to work cross‑functionally.
• Curiosity and passion for emerging AI technologies.

Preferred Qualifications:

• Experience building or securing generative AI applications.
• Knowledge of frameworks like NIST AI RMF, OWASP LLM Top 10, MITRE ATLAS, ISO/IEC 42001.
• Cloud or AI‑related certifications.
• Background in ML engineering or MLOps.

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