AI Engineer

Your role in the team We are seeking an AI Developer who is a fast learner and rapid problem solver, capable of quickly understanding new domains, technologies, and business problems, and translating them into high impact proof of concept (PoC) solutions. This role requires the ability to move quickly from idea to working prototype, validate value early, and then guide successful PoCs into scalable, production ready AI solutions. In this role, you will be a hands-on developer —pairing daily with other engineers and guiding adoption of LLMs, RAG, vector stores, and agentic frameworks. You’ll partner closely with product and platform leaders to build AI systems.

• Work in a highly talented diverse team.

• Be encouraged to continuously learn new skills, technologies, and tools.

• Identify areas for innovation and have the freedom to rapidly explore and test out your ideas.

• Play a critical role in the design, development, and deployment of AI/ML tools.

• lead the effort in taking AI/ML solutions from proof-of-concept to production-ready state. An ideal candidate should demonstrate:

• Deep understanding of machine leaning fundamentals and ability to apply them in developing and implementing AI/ML solutions.

• Experience with GenAI technologies and techniques (e.g., RAG, fine-tuning, vector stores, Agentic frameworks).

• Solid grasp of software development principles, including design patterns, testing, and version control such as Git.

• Inquisitive nature, with a deep understanding of both technical and business aspects.

• Data-driven decision maker, combining robust analytical thinking with sound business judgment.

• Excellent communicator with both technical and non-technical team members.

• Comfortable with hands-on involvement in AI/ML experimentation and model development. Responsibilities include (but are not limited to):

• Participate in projects, demonstrating technical expertise and a hands-on approach in experimentation and productization.

• Partner with product stakeholders to iterate quickly on PoCs, incorporating feedback and refining solutions in short cycles.

• Establish and socialize strong AI engineering fundamentals, design patterns, code quality standards Technical Skills Needed 1) Programming & Engineering Excellence

• Python (advanced), APIs, pipelines, and AI orchestration

• Java/ReactJS (optional) 2) LLM & GenAI Engineering

• Hands-on experience with LLMs (preferably GPT models)

• Prompting patterns and structured outputs

• Model evaluation including accuracy/faithfulness checks, hallucination mitigation, regression testing

• Safety/guardrails patterns appropriate for enterprise use 3) Demonstrated ability to leverage GitHub Copilot for code acceleration:

• Rapid scaffolding of code, services, APIs, and development 3) Data Skills — SQL + SQL Server, Microsoft Fabric(optional)

• SQL skills

• Query authoring, joins, indexing awareness

• Ability to design data access patterns for AI 4) LLM & GenAI Engineering

• Hands-on experience with LLMs (commercial)

• Prompting patterns and structured outputs

• Strong experience implementing RAG architecture with ingestion pipelines, chunking strategies

• Vector database / vector search experience with Indexing, similarity search, metadata filtering

• Experience with MCP patterns, Standardizing tool/context access for models and agent runtimes

• Designing MCP servers/tool endpoints and integrating them into LLM apps

• Experience implementing agentic workflows, A2A patterns such as multi-agent collaboration (planner/executor/reviewer/retriever roles) 8) Cloud

• MS Azure Fabric preferred 9) Observability & Production Support

• Experience operating and supporting AI-enabled services in production: o Logging, metrics, tracing (APM tools such as Datadog) o Model/prompt monitoring, drift signals, quality regression detection So, what are the essential criteria to apply?