Agentic AI & GenAI Full Stack Engineer / Architect

Need Immediate Joiner within 15-20days max

Skills: Agentic Coding, AI Architecture, Building GenAI Apps, Full Stack

Stack: Golang, OpenStack, Docker, PostgresDB, MongoDB, JavaScript, Weaviate, OpenAI, Gemini

Tools: Cursor, Windsurf, Codex, Github Copilot, GCP

Job Summary

We are seeking a highly skilled Agentic AI & GenAI Fullâ€`Stack Engineer / Architect to design, build, and scale nextâ€`generation agentâ€`driven AI systems and Generative AI applications. This role blends AI architecture, agentic coding patterns, LLM application development, and fullâ€`stack engineering to deliver intelligent, autonomous, and productionâ€`grade AI solutions.

You will be responsible for architecting AIâ€`first platforms, building multiâ€`agent systems, integrating LLMs into fullâ€`stack products, and ensuring enterpriseâ€`grade scalability, security, and observability.

Key Responsibilities

Agentic AI & Intelligent System Design

Design and implement agentic AI systems using planners, tools, memory, reflection, and orchestration patterns.

Build multiâ€`agent architectures for task decomposition, collaboration, and autonomous execution.

Implement reasoning loops such as ReAct, Planâ€`Execute, Toolâ€`Use, and Selfâ€`Reflection.

Evaluate and optimize agents for accuracy, latency, cost, and safety.

GenAI Application Development

Design and develop LLMâ€`powered applications including chatbots, copilots, workflow automation tools, and knowledge assistants.

Implement advanced RAG pipelines (vector search, reâ€`ranking, hybrid retrieval, metadata filtering).

Integrate structured outputs, function/tool calling, and prompt orchestration frameworks.

Apply prompt engineering, prompt versioning, and evaluation techniques.

AI Architecture & Platform Engineering

Define endâ€`toâ€`end AI system architectures covering model APIs, orchestration layers, data pipelines, and serving infrastructure.

Architect scalable solutions using cloudâ€`native and microservices patterns.

Design model lifecycle workflows including experimentation, monitoring, feedback loops, and continuous improvement.

Establish patterns for AI governance, observability, security, and cost management.

Fullâ€`Stack Development

Build endâ€`toâ€`end applications covering frontend, backend, and AI orchestration layers.

Develop responsive UIs for AIâ€`driven workflows and conversational experiences.

Design and implement highâ€`performance APIs for GenAI services.

Integrate authentication, authorization, logging, and telemetry across the stack.

Enterprise Readiness & Best Practices

Ensure solutions meet enterprise security, compliance, and dataâ€`privacy standards.

Implement monitoring for hallucinations, drift, and agent failures.

Collaborate with product, data, security, and platform teams.

Mentor engineers and contribute to AI engineering standards and reference architectures.