AI Engineer

Role - AI Engineer : Typescript and Python, Gen AI, Agentic AI

Experience Required - 6+ Years

Role Overview: Design, develop, and deploy scalable AI/ML and GenAI solutions to solve complex business problems. Work closely with data scientists, business stakeholders, and cloud teams to build production-grade AI systems.

Must Have Technical/Functional Skills

• 6+ years of experience building large-scale distributed systems + strong experience with LLM systems, agentic workflows or advanced ML infrastructure, async processing, queues, and streaming systems

• Experience working on Typescript and Python, Gen AI, Agentic AI

• Advanced proficiency in Python, Hands-on experience with PyTorch, TensorFlow, Hugging Face.

• Practical knowledge of model orchestration frameworks (e.g., LangChain, LlamaIndex, CrewAI), Familiarity with vector databases

• Experience with cloud platforms (AWS, Azure AI, Google Cloud Vertex AI) and containerization technologies

• Proven ownership of complex, cross-cutting agentic systems spanning multiple teams or products.

• Strong engineering fundamentals across backend systems, APIs, data pipelines, and cloud infrastructure.

• Deep experience across the agentic AI stack, including planning, tool use, memory, and evaluation.

• Fluency with AI-assisted and agentic development workflows.

• Ability to influence technical direction and align teams without formal authority.

• Problem-solving, cross-functional collaboration, and the ability to articulate complex AI concepts to non-technical business stakeholders

Roles & Responsibilities

• Drive technical direction for agentic AI initiatives, influencing architecture patterns, autonomy boundaries, and system design.

• Design, build, and operate production-grade agentic AI systems used across multiple products.

• Own and evolve shared agentic AI capabilities, including:

• Design and Develop Agent frameworks and orchestration layers

• Planning, tool use, and memory strategies

• Design Retrieval and grounding (RAG) pipelines

• LLM infrastructure, inference, and model gateways

• Evaluation, observability, and safety tooling for autonomous systems

• Lead technical design reviews and help teams navigate tradeoffs involving autonomy, safety, reliability, scalability, and cost.

• Partner across teams to deliver complex, cross-cutting agentic AI initiatives from concept to production.

• Evaluate emerging models, techniques, and agentic patterns and translate them into practical, enterprise-ready improvements.