Senior Agentic AI Engineer (Python)_
Why This Role Stands Out
You'll be at the forefront of designing and deploying cutting-edge enterprise-grade AI agents and multi-agent systems, with significant opportunities for impact and skill development in Generative AI and LLMs. This role is ideal for experienced Python engineers passionate about building scalable AI solutions and contributing to a reputable technology company. Don't miss this chance to advance your career and shape the future of intelligent automation.
Quick Overview
Job Description
Senior Agentic AI Engineer (Python)
Experience:5 10 years
Location:Onsite / Offshore (Flexible)
Primary Objective
We are seeking a Senior Agentic AI Engineer to design, build, deploy, and operate enterprise-grade AI agents and multi-agent systems. The role focuses on Generative AI, LLMs, agentic workflows, RAG architectures, AI orchestration, and governed enterprise AI platforms delivering scalable copilots, intelligent automation, and knowledge systems across onshore and offshore delivery environments.
Success looks like:production-ready agents with measurable reliability, governed RAG integrated into enterprise systems, and clear observability/guardrails for business use cases.
Key Responsibilities
Primary
- Design, develop, and deploy AI agents and multi-agent workflows using Python and agentic frameworks (e.g., LangChain, LangGraph, or equivalent).
- Build enterprise-scale RAG solutions over structured and unstructured data sources.
- Develop agent orchestration workflows integrating models, tools, APIs, and enterprise services.
- Build AI-powered copilots, assistants, and automation solutions for enterprise use cases.
- Implement AI monitoring, observability, tracing, telemetry, and performance measurement.
Also expected
- Implement agent memory patterns (short-term, long-term, episodic).
- Integrate agents with enterprise platforms (APIs, databases, SharePoint, Confluence, Salesforce, knowledge repositories).
- Contribute to AI governance: guardrails, security controls, policy enforcement, and compliance.
- Optimize prompts, reasoning strategies, workflows, and execution performance.
- Collaborate with Data Science and ML teams on evaluation, optimization, and continuous improvement.
Must-Have Experience & Skills
- 5 10 years of software engineering experience with strong Python expertise.
- 3+ years designing and implementing AI/ML solutions.
- Hands-on experience building Generative AI applications using LLMs, RAG, and agentic frameworks (LangChain/LangGraph or equivalent; OpenAI SDK or similar).
- Experience delivering enterprise-grade AI solutions in production.
- Experience with distributed onshore/offshore team delivery.
- Solid API/service engineering fundamentals (REST/async services, integration patterns).
- Practical understanding of AI observability, evaluation, and production reliability.
Preferred Skills
- Cloud AI platforms (Azure OpenAI, AWS Bedrock, Google Vertex AI, or similar).
- Vector databases / search (pgvector, OpenSearch, Pinecone, Weaviate, or similar).
- LLMOps tooling (tracing, eval harnesses, prompt/version management).
- Enterprise integrations (SharePoint, Confluence, Salesforce).
- Containerized deployment practices (Docker; Kubernetes a plus).
- AI security, PII handling, and guardrail frameworks.
Soft Skills
- Clear written and verbal communication with technical and business stakeholders.
- Ability to own delivery end-to-end in a distributed team model.
- Pragmatic trade-off judgment between speed, quality, cost, and governance.
Skills
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