Senior Consultant, AI Business Solutions

Microsoft Microsoft · Big Tech · Hyderabad, TS, IN +1 · Technology Consulting

Senior Consultant, AI Business Solutions at Microsoft, focusing on co-engineering GenAI and agentic solutions for customers on Microsoft platforms. The role involves translating ambiguous business needs into working prototypes and production-ready solutions, with an emphasis on end-to-end delivery, risk mitigation, and evaluation of AI outputs. Requires strong engineering and consulting skills to deliver measurable business outcomes.

What you'd actually do

  1. Embed with customer stakeholders to understand business workflows, constraints, and success metrics; translate ambiguous needs into clear requirements, solution hypotheses, and sprint deliverables for GenAI/agentic scenarios.
  2. Design and implement agentic and GenAI solutions on Microsoft platforms (e.g., Dynamics 365, M365 Copilots, Power Platform, Azure) including integrations, APIs, and automations that accelerate adoption and deliver measurable outcomes.
  3. Prototype rapidly, then harden to production: build POCs for agentic workflows (multi-step tasks, tool-use, orchestration), validate with users, and evolve to production-ready implementations with testing, monitoring, and secure deployment patterns.
  4. Own end-to-end delivery from architecture through implementation: define build/test specifications, create eval and quality gates for GenAI outputs, and produce operational guides/runbooks for reliability, safety, and maintainability.
  5. Identify and mitigate business/technical risks specific to AI systems (data access, prompt injection, hallucinations, privacy, compliance, latency, cost); propose safeguards and fallback behaviors for agentic flows.

Skills

Required

  • Experience delivering enterprise-scale solutions on Microsoft platforms (Dynamics 365 / M365 Copilot/ Power Platform / Azure)
  • Experience with integration, security, and deployment in customer environments
  • Experience delivering production software solutions

Nice to have

  • Experience building or extending solutions involving Copilots, AI‑assisted workflows, or intelligent automation
  • Experience building AI-infused workflows (recommendations, summarization, case routing, contact center assist, sales/service copilots) with production-grade engineering practices
  • Experience delivering Dynamics 365 CE/Power Platform solutions, M365 Copilot Solutions

What the JD emphasized

  • co-engineering GenAI and agentic solutions
  • rapid, iterative delivery cycles
  • responsible AI solutions
  • security, compliance, and operational readiness
  • production-grade solutions
  • AI-infused workflows
  • Copilots, AI‑assisted workflows, or intelligent automation

Other signals

  • co-engineering GenAI and agentic solutions
  • rapid, iterative delivery cycles
  • responsible AI solutions
  • security, compliance, and operational readiness
  • translate ambiguous requirements into working software
  • integrate with real customer environments
  • own outcomes through deployment and stabilization
  • build POCs for agentic workflows (multi-step tasks, tool-use, orchestration)
  • validate with users, and evolve to production-ready implementations
  • testing, monitoring, and secure deployment patterns
  • own end-to-end delivery from architecture through implementation
  • create eval and quality gates for GenAI outputs
  • produce operational guides/runbooks for reliability, safety, and maintainability
  • identify and mitigate business/technical risks specific to AI systems (data access, prompt injection, hallucinations, privacy, compliance, latency, cost)
  • propose safeguards and fallback behaviors for agentic flows
  • support deployment and live stabilization
  • troubleshoot integrations and model behavior in real environments
  • iterate quickly
  • ensure successful go-live with clear ownership, monitoring, and incident playbooks
  • balance platform configuration with extensibility
  • maximize speed and maintainability
  • co-engineer with customer teams
  • ensure knowledge transfer, documentation, and reusable patterns
  • drive delivery plans across the full lifecycle—discovery, build, eval, deployment, and operations
  • accounting for dependencies across data, security, and enterprise systems
  • build agentic workflows that invoke tools/APIs safely (function calling patterns)
  • with guardrails, validation, and auditability
  • implement evaluation strategies (offline/online) to measure output quality, groundedness, safety, and business impact
  • capture repeatable assets (templates, reference architectures, accelerators)
  • share feedback loops with internal teams
  • AI-infused workflows (recommendations, summarization, case routing, contact center assist, sales/service copilots)
  • building or extending solutions involving Copilots, AI‑assisted workflows, or intelligent automation