Lead IT Software Engineer

We are seeking an experienced AI Engineer to design, build, and scale AI-driven solutions and autonomous agents that integrate with enterprise platforms such as Salesforce, ERP systems, Microsoft 365/SharePoint, HR platforms, data warehouses, and other cloud services, and establish measurable quality and adoption outcomes. The ideal candidate has hands-on experience delivering real-world AI initiatives, building agent-based workflows using Microsoft Copilot, OpenAI/ChatGPT, Google Agentspace, or similar frameworks, and operationalizing AI within enterprise IT ecosystems.

This role will work closely with engineering, architecture, product, security, and business stakeholders to translate business use cases into production-ready AI solutions with appropriate governance, scalability, and security.

Key Responsibilities

AI Solution Design & Development

• Design, develop, and deploy Agentic Solutions that automate, orchestrate, or augment business workflows across enterprise platforms and ensure production-grade performance through rapid iteration and troubleshooting
• Build agentic workflows using tools such as:
• Microsoft Copilot Studio / Azure OpenAI
• OpenAI (ChatGPT / Assistants / GPT APIs)
• Google Agentspace / Vertex AI
• LangChain, Semantic Kernel, or similar orchestration frameworks
• Implement multi-step reasoning, tool calling, retrieval-augmented generation (RAG), and decision logic within AI agents
• Develop APIs and backend services to support AI-driven workflows

• Integrate AI solutions with enterprise systems, including:
• Salesforce (Sales Cloud, Service Cloud, CPQ, Revenue Cloud, custom Apex APIs)
• ERP systems (MS Dynamics 365, or similar)
• Microsoft 365 / SharePoint / Teams
• Enterprise Data Warehouses, document repositories, and internal APIs
• Enable secure access to structured and unstructured enterprise data for AI use cases
• Design event-driven or workflow-based AI integrations (e.g., case handling, opportunity lifecycle, billing events)

• Contribute to enterprise AI architecture standards, patterns, and best practices
• Implement prompt management, versioning, and testing strategies
• Ensure AI solutions meet security, privacy, and compliance requirements (PII handling, data residency, access control)
• Apply AI guardrails, validation rules, and safety controls to prevent hallucinations or misuse
• Develop evaluation approaches and optimize solutions for accuracy, latency, reliability, and cost.
• Implement production observability and contribute to runbooks and incident response processes for AI services.

• Partner with product managers, architects, platform teams, and business stakeholders to refine AI use cases
• Document solution designs, integration approaches, and operational runbooks
• Support PoCs, pilots, and production rollouts of AI initiatives
• Provide knowledge transfer and technical guidance to internal teams

• 8+ years of experience in software engineering
• 3+ years building & deploying AI/ML or Gen AI solutions that delivery measurable business results in production.
• Experience delivering AI solutions in regulated or large enterprise environments
• Hands-on experience building AI solutions using one or more of:
• Microsoft Copilot / Copilot Studio
• OpenAI (ChatGPT, Assistants API)
• Google Agentspace / Vertex AI
• Strong proficiency with LLM application patterns
• Prompt engineering
• Tool/function calling
• RAG architectures
• Agent orchestration and workflow chaining
• Proficiency in one or more programming languages:
• Python, JavaScript/TypeScript, Java, or C#
• Experience with REST APIs, event-based integrations, and microservices
• Familiarity with cloud platforms (Azure, GCP, or AWS)

• Hands-on integration experience with at least one major enterprise platform:
• Salesforce
• ERP systems (MS Dynamics 365, etc.)
• Microsoft 365 / SharePoint / Teams
• Enterprise Data Warehouses
• Strong understanding of enterprise security, authentication (OAuth, SSO), and role-based access control
• Experience working with enterprise data models and large-scale production systems

• Experience with Salesforce Apex, Flow, Platform Events, or Salesforce APIs
• Experience implementing AI governance frameworks or model risk controls
• Exposure to CI/CD pipelines for AI and backend services
• Familiarity with LLM evaluation frameworks, test automation, or AI monitoring tools
• Experience working with global, distributed teams