AI Software Engineer

We are seeking an experienced
AI Software Engineer
to design, build, and integrate
AI-powered features
into enterprise applications. The ideal candidate will have hands-on experience with
LLMs (Large Language Models)
,
API integrations
, and
AI agent frameworks
, along with strong software engineering and collaboration skills.

Key Responsibilities

• Develop and integrate AI-powered features such as conversational interfaces, insights dashboards, and semantic search.
• Collaborate with Prompt Engineers to optimize prompts and ensure reliable AI outputs.
• Design and orchestrate AI agents, connecting LLMs to APIs and internal tools using frameworks like MCP Server and A2A protocols.
• Implement and maintain observability and compliance integrations (APM, logging, audit pipelines).
• Build and maintain semantic search pipelines, knowledge graphs, and contextual data features.
• Contribute to internal AI libraries, reusable components, and integration standards.
• Support and enhance AI infrastructure for scalability, token control, and API rate management.

Mandatory Skills & Qualifications

• 3+ years of hands-on software development experience in
  AI, NLP,
  or
  data-driven environments.
• Proficiency in Python, .NET, or JavaScript, and REST APIs.
• Hands-on experience with
  LLMs
  (e.g., GPT, Claude, Gemini)
  and integrating them into applications.
• Experience extending
  ChatGPT custom GPTs via Actions
  or similar frameworks.
• Familiarity with
  APM tools
  ,
  log tracing
  , and building
  secure, observable services
  .
• Exposure to
  AI agent orchestration
  ,
  semantic search
  , or
  knowledge graph pipelines
  .
• Understanding of
  A2A protocols
  ,
  MCP Server
  , and
  enterprise integration patterns
  .
• Strong collaboration and communication skills to work cross-functionally with Product, Data, and Engineering teams.

Preferred Skills

• Experience
  building AI Agents
  using platforms like ChatGPT, Gemini, or Claude.
• Knowledge of
  LangChain
  ,
  Semantic Kernel
  , or other agent frameworks.
• Familiarity with
  vector databases
  (Elastic, Pinecone) and
  RAG (Retrieval-Augmented Generation)
  methods.
• Experience developing
  UIs for AI features
  (chat interfaces, dashboards, analytics views).
• Understanding of
  DevOps for AI pipelines
  , including model versioning and prompt testing.
• Experience automating
  AI/LLM evaluation pipelines
  and using frameworks like
  OpenAI Evals
  ,
  LangChain
  , or
  MLflow
  for model testing and validation.