Job Summary

Develop complex Agentic AI solutions in an Agile environment as part of a global team of engineers, architects, designers, and product experts.

· Design, develop, and deploy AI agents, and intelligent workflows using Microsoft Copilot Studio, Claude APIs, and enterprise AI platforms.

· Conduct and lead technical design discussions across multiple technology disciplines to propose viable AI and automation solutions to complex business problems.

· Develop and build strong relationships across the business to effectively influence and accomplish strategic objectives.

· Assist on-shore and off-shore teams with issues requiring expertise in AI agent orchestration, prompt engineering, enterprise integrations, and cloud-native architecture. Mentor and develop new or less experienced team members.

· Liaise between software engineering teams and production support to facilitate operational readiness. Provide required support for escalated issues and AI solution defects.

· Work with engineering and testing teams to coordinate non-production deployments and AI solution validation activities.

· Partner with Release Management teams for production deployments of AI-powered capabilities.

· Partner with SaaS platform providers and AI vendors to deliver program capabilities.

· Coordinate enterprise changes and integrations impacting AI agents, knowledge sources, APIs, and enterprise systems.

· Oversee AI governance, Responsible AI practices, security reviews, and compliance processes.

· Analyze application logs and telemetry (Splunk, CloudWatch, AppDynamics, ArgoCD, Copilot analytics, AI monitoring tools) to identify root causes and optimize AI solution performance.

· Create monitoring, observability, alerts, and operational dashboards for AI solutions.

· Build and maintain deployment, release, and governance processes for AI platforms and agentic solutions.

· Design and implement Retrieval-Augmented Generation (RAG) architectures and integrate enterprise knowledge sources.

· Develop prompt engineering strategies, agent orchestration workflows, and human-in-the-loop business processes.

· Evaluate and optimize AI agent performance, response quality, accuracy, and adoption metrics.

Key Responsibilities

Bachelor’s degree in computer science, Engineering, Artificial Intelligence, or related field.

· 5+ years of professional software engineering or enterprise technology experience.

· 2+ years of experience building AI-powered applications, intelligent automation, or conversational AI solutions.

· Experience with Agentic AI platforms including AWS Agentcore, Bedrock, Microsoft Copilot Studio, Claude, or similar LLM-based platforms.

· Experience with enterprise integration technologies including Microsoft Graph API, REST APIs, Dataverse, SharePoint, Teams, and SaaS platforms.

· Experience designing and implementing Retrieval-Augmented Generation (RAG) on postgres solutions and knowledge-grounded AI experiences.

· Experience with prompt engineering, agent orchestration, AI workflows, function calling, and enterprise AI governance.

· Experience with secure software development practices, Responsible AI principles, and cloud security standards.

· Experience leveraging AI-assisted development tools such as GitHub Copilot, Claude code (building skills, plugin, MCP), or equivalent AI coding assistants.

· Experience with cloud technologies including AWS, Docker, EKS, Lambda, SNS/SQS, and cloud-native architectures.

· Experience with source control and development workflows including GitHub, BitBucket, Git.

· Experience with logging, monitoring, and observability tools such as AppDynamics, ArgoCD, CloudWatch, Splunk, and enterprise AI monitoring solutions.

· Experience evaluating AI solution quality, automation effectiveness, and operational performance.

· Familiarity with vector databases, semantic search, knowledge management platforms, and enterprise AI architectures.

· Proven ability to convert ideas into Agentic solution and deliver results in a fast-paced Agile environment.

· Proven track record of developing and supporting large-scale business-critical platforms and enterprise solutions.

· Excellent analytical and problem-solving skills with the ability to evaluate AI outputs, identify risks, and recommend improvements.

· Must be comfortable in a fast-paced, evolving technology landscape.

· Strong presentation, communication, and collaboration skills with the ability to create and maintain technical documentation and architectural artifacts.

Preferred Qualifications

· Experience with Microsoft Copilot Studio, Claude, and AWS Bedrock.

· Experience implementing multi-agent orchestration and agentic workflow patterns.

· Experience with Python, ReactJS, LangChain, Semantic Kernel, MCP (Model Context Protocol), or AI orchestration frameworks.

Skill Requirements

Insurance, Financial Services, Healthcare, or other highly regulated industry experience.

· Experience establishing enterprise AI governance, AI Centers of Excellence, or Copilot adoption programs.

· Experience building employee productivity intelligent assistants, or enterprise knowledge agents.

· Microsoft AI-102, PL-400, PL-600, AWS AI Practitioner, or equivalent AI/Cloud certifications is a plus.

Other Requirements

· Insurance, Financial Services, Healthcare, or other highly regulated industry experience.

· Experience establishing enterprise AI governance, AI Centers of Excellence, or Copilot adoption programs.

· Experience building employee productivity intelligent assistants, or enterprise knowledge agents.

· Microsoft AI-102, PL-400, PL-600, AWS AI Practitioner, or equivalent AI/Cloud certifications is a plus.