AI Solutions Architect

VirtusaPiscataway, NJ

About The Position

The AI Solutions Leader defines the technical direction for AI, ML, and data-driven capabilities across the enterprise. The role shapes the architecture for intelligent, cloud-native solutions leveraging machine learning, LLMs, automation, and modern data platforms while ensuring security, scalability, compliance, and operational resilience.

Requirements

  • Hands on experience in LangChain & LangGraph 1.2.x
  • Good understanding on agentic design patterns (workflows and multi agentic patterns - supervisor, sub agents and swarm)
  • Writing evaluations to agentic systems. (Metric based and LLM as judge)
  • Hands on experience in MCP servers and MCP clients.
  • Develop and deploy AI solutions using Python, Java, and frameworks like FastAPI, integrating with APIs and App Engine.
  • Implement and manage CI/CD pipelines for efficient and secure deployment.
  • Ensure secure handling of API keys, passwords, and tokens across environments.
  • Use Docker for containerization and GitHub for version control and collaborative development.
  • Conduct testing of AI agents and workflows to ensure reliability, accuracy, and performance.
  • Collaborate with cross-functional teams to identify business problems and apply AI-driven solutions.

Nice To Haves

  • Azure AI foundry stack
  • Azure AI search: semantic, keyword & hybrid search
  • Azure document intelligence
  • Multi-threading in Python
  • AsyncIO
  • Non blocking programming.

Responsibilities

  • Act as a subject matter expert and internal champion for AI capabilities.
  • Lead end-to-end solutioning of AI agents and agentic workflows, including design, development, testing, and deployment.
  • Build business cases, conduct process reviews, perform data analysis, and document business requirements.
  • Apply prompt and context engineering techniques to optimize AI model performance.
  • Work with cutting edge Generative AI models such as OpenAI (ChatGPT), Anthropic, Microsoft, and Meta (LLaMA).
  • Develop and deploy AI solutions using Python, Java, and frameworks like FastAPI, integrating with APIs and App Engine.
  • Implement and manage CI/CD pipelines for efficient and secure deployment.
  • Ensure secure handling of API keys, passwords, and tokens across environments.
  • Use Docker for containerization and GitHub for version control and collaborative development.
  • Conduct testing of AI agents and workflows to ensure reliability, accuracy, and performance.
  • Collaborate with cross-functional teams to identify business problems and apply AI-driven solutions.
  • Mentor Operations staff on AI solutioning, prompt design, and best practices.
  • Drive AI adoption across the Operations Practice through enablement sessions, bootcamps, and strategic initiatives.
  • Execute rapid response AI projects with a focus on delivery and measurable business impact.
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