Website:
cittaai.com
Job details:
1. Position Information
Job Title: Software Consultant – AI & GenAI (Azure Agentic Ops)
Department: Engineering – Agentic AI
Reporting To: Delivery Manager
Employment Type: Full-Time Work
Location: Onsite
Experience: 5–8 Years
2. Role Overview
We are seeking a highly motivated Software Consultant – AI & GenAI to lead the implementation and governance of an AI-powered Software Development Life Cycle (SDLC) transformation initiative built on Microsoft Azure Agentic Ops.
In this role, you will design, govern, and drive delivery of intelligent AI agents that automate and enhance SDLC activities including requirements analysis, solution design, code generation, code review, testing, documentation, deployment, and operational support.
You will collaborate with software engineers, AI engineers, architects, QA, and business stakeholders to ensure AI solutions are secure, scalable, production-ready, and aligned with enterprise engineering standards.
3. Key Responsibilities
- Lead AI-driven SDLC automation using Azure Agentic Ops.
- Design multi-agent architectures for software engineering workflows.
- Provide technical leadership to engineering teams developing AI agents.
- Review, validate, and approve AI agent implementations before production deployment.
- Establish AI governance, engineering standards, and security best practices.
- Mentor engineering teams on AI engineering, prompt engineering, and responsible AI.
- Design RAG solutions and enterprise AI integrations.
- Optimize prompts, agent workflows, and model performance.
- Collaborate with DevOps on CI/CD for AI applications.
- Drive enterprise adoption of AI-assisted software development.
4. Technical Expertise
AI & GenAI:
- Large Language Models (LLMs)
- Agentic AI & Multi-Agent Systems
- Azure Agentic Ops
- Retrieval-Augmented Generation (RAG)
- AI Evaluation & Observability
- Responsible AI
- Human-in-the-Loop (HITL)
Microsoft Azure:
- Azure AI Foundry
- Azure OpenAI Service
- Azure AI Search
- Azure Functions
- Azure App Services
- Azure Storage
- Azure Key Vault
- Azure Monitor
- Azure DevOps
- Azure Kubernetes Service
Software Engineering:
- Python
- REST APIs
- Microservices
- Event-Driven Architecture
- Distributed Systems
- Secure SDLC
- Git & CI/CD
Frameworks:
- Langchain
- Model Context Protocol (MCP)
- Vector Databases
- Embedding Models
5. Functional Competencies
Enterprise Solution Architecture, AI Solution Design, Technical Governance, SDLC Transformation, AI System Integration, Software Quality Assurance, Performance Optimization, Documentation, Risk Assessment, Engineering Process Improvement.
6. Consulting Competencies
Lead stakeholder engagements, translate business requirements into scalable AI solutions, provide technical consulting, conduct architecture reviews, support delivery governance, and drive AI engineering best practices.
7. Communication & Collaboration
Excellent communication, stakeholder management, mentoring, cross-functional collaboration, and the ability to communicate AI concepts to both technical and non-technical audiences.
8. Required Qualifications
- Bachelor's or master's degree in computer science, IT, AI, or related field.
- 5–8 years of software engineering experience.
- Hands-on Azure cloud experience.
- Experience building enterprise AI/GenAI solutions.
- Experience leading technical teams.
9. Preferred Qualifications
- Azure AI certifications,
- Azure Solutions Architect certification,
- Experience with Azure Agentic Ops,
- Enterprise RAG implementations,
- Responsible AI,
- MLOps/LLMOps.
10. Professional Skills
Technical Leadership, Strategic Thinking, Problem Solving, Stakeholder Management, Mentoring, Collaboration, Innovation, Accountability.
11. Tools & Technologies
Azure AI Foundry, Azure OpenAI, Azure Agentic Ops, Azure AI Search, Azure DevOps, LangChain, Python, Git, GitHub, Docker, Kubernetes, VS Code, Jira, Confluence.
12. Success Measures (KPIs)
Delivery of AI-powered SDLC capabilities, quality of deployed AI agents, engineering productivity improvements, reduced manual effort, AI governance compliance, stakeholder satisfaction, and continuous optimization.
13. Career Growth Opportunities
AI Solution Architect, Principal AI Consultant, Engineering Manager – AI, Enterprise AI Architect, AI Practice Lead.
14. Why Join Us
Lead enterprise-scale AI transformation initiatives using Microsoft Azure AI technologies and shape the future of intelligent software engineering through secure, scalable, production-ready Agentic AI solutions.
Key Skills
- AI & GenAI: LLMs, Agentic AI, Azure Agentic Ops, RAG, Prompt Engineering, HITL
- Cloud: Azure AI Foundry, Azure OpenAI, Azure AI Search, Azure
- DevOpsProgramming: Python, REST APIs, Microservices
- Frameworks: LangChain, Semantic Kernel, AutoGen, MCP
- DevOps: Git, Docker, Kubernetes, CI/CD
- Leadership: Technical Leadership, Solution Architecture, AI Governance, Team Mentoring
Click on Apply to know more.