Staff Engineer, Generative AI Engineer

Jobgether; India; On-site; INR 4,000,000 - 6,000,000; Full time

Job summary

Jobgether is seeking a Staff Engineer for Generative AI based in India to design, build and scale enterprise-grade AI solutions. You will lead multi-agent architectures, RAG pipelines, and AI governance while mentoring teams and shaping production AI architectures.

The role blends hands-on development with technical leadership across cloud, security, observability, and enterprise integration, using Python, FastAPI, LLMs, and modern AI platforms.

Qualifications

• 5.5+ years of professional experience in AI/Generative AI engineering.
• Bachelor’s or master’s in Computer Science, IT, or related field.
• Strong hands-on Python and production-grade GenAI development.
• Experience with FastAPI for scalable, secure APIs.
• Knowledge of LLMs, embeddings, vector databases, and retrieval optimization.
• Experience designing enterprise AI agents, conversational AI, and agentic AI solutions.
• Experience with LangGraph, CrewAI, Temporal, or similar frameworks.
• Experience integrating AI agents with REST APIs, MCP, and A2A protocols.
• Familiarity with Azure OpenAI and AWS Bedrock.
• CI/CD, Docker, Kubernetes, Azure DevOps, Argo CD, GitOps.
• AI security, OAuth2/JWT, guardrails, governance.
• Observability and monitoring tools like LangSmith, OpenTelemetry, Elasticsearch.

Responsibilities

• Design, develop, and deploy enterprise-grade Generative AI, Agentic AI, AI agent, and conversational AI solutions.
• Architect multi-agent systems including workflows, reasoning, memory, tool integrations, orchestration and coordination.
• Design and optimize scalable RAG pipelines (document processing, embeddings, vector search, retrieval, grounding, response generation).
• Develop and refine LLM prompts, retrieval strategies, agent workflows, and AI responses.
• Integrate AI agents with enterprise systems via REST APIs, MCP, and A2A protocols.
• Build secure, scalable cloud-native AI apps using OAuth2/JWT, Key Vault, guardrails, and governance controls.
• Maintain CI/CD and GitOps pipelines with Azure DevOps, Docker, Kubernetes, Argo CD.
• Implement testing, AI evaluation, observability, monitoring, logging, and tracing (LangSmith, OpenTelemetry, Elasticsearch).
• Optimize AI apps for performance, scalability, reliability, latency, and cost efficiency.
• Address security, governance, and operational risks in enterprise AI apps.
• Collaborate with business, engineering, platform, security and cloud teams to translate requirements into scalable AI solutions.
• Evaluate emerging LLMs and AI frameworks; recommend technologies to improve AI ecosystem.
• Provide technical leadership and mentor engineers on GenAI, LLM apps, and production AI engineering.

Skills

Python

FastAPI

LLMs

Prompt engineering

RAG

Embeddings

Vector databases

Multi-agent systems

REST APIs

OAuth2/JWT

Education

Bachelor's or Master's in CS/IT or related

Tools

LangGraph

CrewAI

Temporal

Azure DevOps

Docker

Kubernetes

Argo CD

OpenTelemetry

Job description

This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for a Staff Engineer, Generative AI Engineer based in India.

This is a senior technical role focused on designing and delivering enterprise-grade Generative AI solutions at scale. You will build AI agents, conversational systems, multi-agent architectures, and RAG-powered applications using modern AI engineering practices. The role combines hands‑on development with technical leadership across cloud, security, orchestration, observability, and enterprise integration. You will work with technologies such as Python, FastAPI, LLMs, vector databases, LangGraph, CrewAI, Temporal, and enterprise AI platforms. The position offers the opportunity to shape production AI architectures while solving complex problems around reliability, scalability, security, and cost efficiency. You will collaborate closely with engineering, cloud, security, platform, and business teams in a dynamic, global, and non‑hierarchical environment. As a Staff-level engineer, you will also influence technical direction and mentor teams advancing the organization's GenAI capabilities.

Accountabilities:

• Design, develop, and deploy enterprise-grade Generative AI, Agentic AI, AI agent, and conversational AI solutions using Python and FastAPI.
• Architect and implement multi-agent systems, including workflows, reasoning, memory, tool integrations, orchestration, and agent coordination.
• Design and optimize scalable RAG pipelines, covering document processing, chunking, embeddings, vector search, retrieval, grounding, and response generation.
• Develop and refine LLM prompts, retrieval strategies, agent workflows, and AI responses to maximize accuracy, reliability, relevance, and business value.
• Integrate AI agents with enterprise applications through REST APIs, MCP, and A2A protocols.
• Build secure, scalable cloud-native AI applications using technologies such as OAuth2/JWT, Key Vault, Responsible AI guardrails, and governance controls.
• Develop and maintain CI/CD and GitOps pipelines using Azure DevOps, Docker, Kubernetes, Argo CD, and related technologies.
• Establish robust approaches to testing, AI evaluation, observability, monitoring, logging, and distributed tracing, leveraging tools such as LangSmith, OpenTelemetry, and Elasticsearch.
• Optimize AI applications for performance, scalability, reliability, latency, cost efficiency, and production readiness.
• Identify and address security, governance, and operational risks associated with enterprise AI applications.
• Collaborate with business, engineering, platform, security, and cloud teams to translate business requirements into scalable AI solutions.
• Evaluate emerging LLMs, agentic AI frameworks, AI engineering platforms, and industry practices, recommending technologies that can improve the AI ecosystem.
• Provide technical leadership and mentor engineers on GenAI, LLM applications, RAG architectures, agent design, and production AI engineering.

Requirements:

• 5.5+ years of professional experience, including strong and recent hands‑on experience in AI/Generative AI engineering.
• Bachelor’s or master’s degree in Computer Science, Information Technology, or a related technical field.
• Strong hands‑on expertise in Python and production‑grade AI/GenAI application development.
• Proven experience with FastAPI for building scalable, secure, and production‑ready APIs.
• Strong knowledge of LLMs, prompt engineering, RAG, embeddings, vector databases, and retrieval optimization.
• Hands‑on experience designing and implementing enterprise AI agents, conversational AI, and Agentic AI solutions.
• Experience with agent orchestration frameworks such as LangGraph, CrewAI, Temporal, or comparable technologies.
• Experience integrating AI agents with enterprise systems through REST APIs, MCP, and A2A protocols.
• Familiarity with enterprise LLM platforms such as Azure OpenAI and AWS Bedrock.
• Experience with Docker, Kubernetes, CI/CD, Azure DevOps, Argo CD, and GitOps practices.
• Strong understanding of AI security, OAuth2/JWT, Responsible AI guardrails, governance, and enterprise application security.
• Experience implementing AI evaluation, observability, monitoring, logging, and tracing, preferably using tools such as LangSmith, OpenTelemetry, or Elasticsearch.
• Good-to-have experience with Semantic Kernel, AWS Bedrock AgentCore, and enterprise AI governance.
• Strong analytical and problem‑solving skills, with the ability to work through complex technical challenges.
• Excellent stakeholder management, communication, collaboration, and technical leadership abilities.
• Demonstrated ability to mentor engineers and influence architecture and engineering practices across teams.

Benefits:

• Opportunity to work on cutting‑edge Generative AI and Agentic AI solutions with enterprise‑scale applications.
• Exposure to modern technologies spanning LLMs, RAG, multi‑agent architectures, vector databases, cloud platforms, and AI orchestration.
• Opportunity to take a Staff‑level technical leadership role, influencing architecture and engineering standards.
• Collaboration with multidisciplinary teams across engineering, cloud, security, platform, and business functions.
• Dynamic, global, and non‑hierarchical work environment.
• Opportunities to mentor engineers and contribute to the development of advanced AI engineering capabilities.
• Continuous exposure to emerging AI technologies, frameworks, and industry best practices.
• Professional growth opportunities within a large, globally distributed technology organization.
• Competitive compensation and benefits, subject to the applicable employment package and local policies.