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 using frameworks such as LangGraph, CrewAI, AutoGen, Semantic Kernel, or OpenAI Agents SDK.
• Develop orchestration for planning, checkpointing, retries, fallback handling, and resumable long-running processes.
• Build and optimize RAG pipelines using chunking, embeddings, vector or hybrid search, retrieval evaluation, grounded responses, and citations.
• Develop memory and context-management solutions with short-term and long-term stores and compaction strategies.
• Write Python APIs and services with asynchronous execution, background jobs, and containerized deployments.
• Integrate enterprise systems through MCP, A2A, OpenAPI, REST, and gRPC with graceful degradation and retries.
• Apply security and governance practices including RBAC, prompt safety, traceability, and secrets management.
• Implement evaluation and observability frameworks using tools such as Langfuse, Arize, or OpenTelemetry.
• Contribute to architecture decisions, code reviews, and engineering standards.

Required Qualifications

• Bachelor’s or Master’s degree in Computer Science, Engineering, or a related field.
• Production experience delivering Generative AI or Agentic AI systems.
• Expertise in Python engineering for APIs, microservices, testing, and CI/CD.
• Strong knowledge of LLM capabilities, prompt design, structured outputs, tool calling, and retrieval strategies.
• Hands-on 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, preferably Azure, with Docker and Kubernetes.
• Understanding of schema validation and MLOps tools such as JSON Schema, Pydantic, MLflow, or Airflow.
• Ability to explain cost, latency, and accuracy trade-offs to technical and non-technical audiences.

Preferred Qualifications

• Experience with Azure AI Foundry or Microsoft Agent Framework.
• Knowledge of MCP and A2A protocols for agent and tool interoperability.
• Hands-on experience with Pinecone, Weaviate, Qdrant, or pgvector.
• Familiarity with distributed systems, workflow engines, and event-driven architectures.
• Experience with open-source or small language models, AI safety, governance, or foundation-model adaptation.

Benefits

• End-of-service gratuity, private healthcare, life insurance, and an employee assistance program.
• Wellness program, annual air travel allowance for expatriates, and global travel medical and accident insurance.
• Referral bonuses and learning opportunities including training, coaching, professional certifications, and courses.