Staff Engineer, Generative AI Engineer

This is a fully remote position, open to applicants in India.

📋 Description

• Design, develop, and deploy enterprise-level AI agents, Agentic AI, and conversational AI solutions utilizing Python and FastAPI.

• Build and oversee multi-agent systems, which include workflow orchestration, reasoning, memory management, tool integration, and agent coordination.

• Create and implement scalable RAG-based AI solutions using vector databases, embeddings, and sophisticated prompt engineering techniques.

• Develop and enhance LLM prompts, retrieval strategies, agent workflows, and AI responses to ensure accuracy, reliability, and alignment with business needs.

• Integrate AI agents with enterprise applications via REST APIs, MCP, and A2A protocols.

• Implement secure and scalable cloud-native AI applications, incorporating OAuth2/JWT, Key Vault, Responsible AI guardrails, and governance controls.

• Construct and maintain CI/CD pipelines using Azure DevOps, Docker, Kubernetes, Argo CD, and GitOps methodologies.

• Establish automated testing, observability, monitoring, logging, tracing, and AI evaluation employing tools such as LangSmith, OpenTelemetry, and Elasticsearch.

• Optimize AI solutions for performance, scalability, reliability, latency, cost-effectiveness, and readiness for production.

• Collaborate with business, platform, security, cloud, and engineering teams to deliver enterprise-grade AI solutions.

• Assess and integrate emerging LLMs, Agentic AI frameworks, AI engineering tools, and industry best practices.

• Provide technical leadership and mentor engineering teams on GenAI, LLM applications, RAG, agent architecture, and production AI engineering.

⛳️ Requirements

• Minimum of 5.5 years of total experience, with substantial recent experience in AI/GenAI engineering.

• Strong hands-on experience in Python and the development of production-grade AI/GenAI applications.

• Essential expertise in FastAPI for scalable, secure, and production-ready APIs.

• Significant experience with LLMs, prompt engineering, RAG, vector databases, and embeddings.

• Practical experience in designing and developing enterprise AI agents, conversational AI, and Agentic AI solutions.

• Extensive experience in building RAG pipelines, including document processing, chunking, embeddings, vector search, retrieval, grounding, and response generation.

• Solid knowledge of vector databases and embedding technologies, with experience in optimizing retrieval and relevance.

• Hands-on experience with agent orchestration frameworks such as LangGraph, CrewAI, Temporal, or similar.

• Experience in integrating AI agents with enterprise applications through REST APIs, MCP, and A2A protocols.

• Good understanding of Azure OpenAI, AWS Bedrock, or other enterprise LLM platforms.

• Familiarity with Docker, Kubernetes, CI/CD, Azure DevOps, Argo CD, and GitOps methodologies.

• Strong comprehension of AI security principles, including OAuth2/JWT, Responsible AI guardrails, governance, and enterprise application security.

• Experience with AI evaluation, observability, monitoring, logging, and tracing using tools such as LangSmith, OpenTelemetry, or Elasticsearch.

• Preferred experience with Semantic Kernel, AWS Bedrock AgentCore, and enterprise AI governance.

• Strong analytical, problem-solving, stakeholder management, collaboration, and communication abilities.

• Bachelor’s or master’s degree in computer science, Information Technology, or a related field.

🏝️ Benefits

• Remote work.