Gen AI Developer

Virtusa Corporation
Tampa, FL, United States
4 days ago
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Role details

Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Experience level
Expert
Experience required
10 years minimum
Working hours
Regular working hours

Tech stack

LangGraph Framework Application Programming Interfaces (APIs) Artificial Intelligence Computer Programming Memory Management JSON Language Modeling Open Source Technology OpenAI Openapi Transfer Learning Open-source Models
+14 more
Large Language Models Multi-Agent Systems Google Vertex AI Qwen Caching Generative AI Agentic-AI Optimization Algorithms CrewAI AutoGen Invoking Functions Model Context Protocol Semantic Kernel Human in the Loop

Job description

Citi seeking an experienced and visionary Senior AI Developer specializing in Generative AI, Agentic AIArchitectures, and Enterprise Retrieval-Augmented Generation (RAG) systems. In this role, you will be responsible for designing, building, and deploying cutting-edge AI-powered solutions, multi-agent workflows,and intelligent semantic retrieval pipelines that solve complex enterprise challenges.

You will lead the technical design and end-to-end implementation of scalable Large Language Model (LLM)applications, autonomous agentic systems, vector search backends, and robust evaluation guardrails.

Responsibilities:

  1. Generative AI & LLM Engineering
  • Architect, fine-tune, and deploy foundation model applications utilizing commercial APIs (e.g., OpenAI,Anthropic, Google Vertex AI) and open-source models (e.g., Llama, Mistral, Qwen).
  • Design robust prompt engineering patterns, structured output schemas (JSON/Pydantic validation), modelrouting, and context window management strategies.
  • Implement optimization techniques including parameter-efficient fine-tuning (PEFT/LoRA), quantization,caching, and model distillation for latency and cost efficiency.
  1. Agentic AI & Autonomous Systems
  • Design and orchestrate deterministic and autonomous multi-agent workflows using modern frameworks (e.g.,LangGraph, CrewAI, AutoGen, Semantic Kernel, or custom state-machine engines).
  • Build sophisticated agent capabilities including tool use/function calling, multi-step planning, reflection/self-correction loops, memory management (short-term, long-term, working memory), and human-in-the-loop(HITL) approval gates.Implement protocol standards such as Model Context Protocol (MCP) and OpenAPI-driven tool execution.

Requirements

Artificial Intelligence (AI), Artificial Intelligence (AI), Technical/Engineering Design, Modeling Languages, Application Programming Interface (API), Open Source, JSON, Management Strategy, Caching, Kernel Programming

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