Senior AI Engineer - Agentic AI

Role Overview

Responsibilities

• Design, build, and deploy Generative AI and Agentic AI solutions from prototype to production.
• Implement multi-agent orchestration with frameworks such as LangGraph, CrewAI, AutoGen, Semantic Kernel, or OpenAI Agents SDK.
• Develop workflow orchestration for planning, checkpointing, retries, fallback handling, and long-running process resumption.
• Build RAG pipelines with chunking, embeddings, vector or hybrid search, retrieval evaluation, grounded responses, and citations.
• Develop memory and context management using short-term and long-term stores and compaction strategies.
• Build Python APIs and services with FastAPI, asynchronous execution, background jobs, and containerized deployments.
• Integrate enterprise systems using MCP, A2A, OpenAPI, REST, and gRPC with retries and graceful degradation.
• Apply RBAC, prompt safety, traceability, secrets management, evaluation, and observability practices.
• Contribute to architecture decisions, code reviews, and engineering standards.

Requirements

• Bachelor’s or Master’s degree in Computer Science, Engineering, or a related field; a PhD is a plus.
• Production experience delivering Generative AI or Agentic AI systems.
• Python engineering expertise covering APIs, microservices, testing, and CI/CD.
• Strong knowledge of LLM capabilities, prompt design, structured outputs, tool calling, and retrieval strategies.
• Experience with agent orchestration frameworks such as LangGraph, AutoGen, CrewAI, or Semantic Kernel.
• Experience with RAG, embeddings, and vector database integrations.
• Familiarity with stateful or long-running systems, checkpointing, and resumable workflows.
• Cloud deployment experience with Docker and Kubernetes; Azure is preferred.
• Knowledge of JSON Schema or Pydantic and MLOps tools such as MLflow or Airflow.
• Strong communication skills for explaining cost, latency, and accuracy trade-offs.
• Additional advantages include Azure AI Foundry, MCP, A2A, distributed systems, workflow engines, AI safety, open-source LLMs, or fine-tuning experience.

Benefits

• End of service gratuity, private healthcare, life insurance, and an employee assistance program.
• Wellness program and annual air travel allowance for expatriates.
• Performance feedback, salary reviews, referral bonuses, and learning and development opportunities.
• Training, coaching, professional certifications, and courses are available.