IN_Manager_Gen AI_Data and Analytics_Advisory_Hyderabad

Role Overview 

 The Technical Product Owner / Forward Deployed Engineer operates at the intersection of product strategy, technical solution architecture, and GenAI ecosystem, driving the design, deployment, and optimization of AI-powered solutions within Portfolio Services. This role requires fluency in agentic AI orchestration, enterprise-grade system integration, and cloud-native deployment, ensuring solutions are technically robust, scalable, and aligned with client value delivery.  

Responsibilities 

 Product Strategy & Architecture 

•  Define and maintain the technical product roadmap for AI agents, automation pipelines, and orchestration frameworks. 

•  Translate business requirements into solution architectures with clear data flows, API contracts, and integration points. 

• Develop user stories and acceptance criteria with explicit technical dependencies and performance benchmarks. 

• Balance short-term MVP delivery with long-term scalability, modularity, and extensibility. 

Technical Deployment & Engineering 

• Lead end-to-end deployment of AI/GenAI solutions, including containerization, CI/CD pipelines, and cloud-native rollout. 

• Configure and integrate LangGraph, LlamaIndex, Hugging Face models, TensorFlow/PyTorch pipelines into enterprise workflows. 

• Implement data ingestion pipelines, vector databases (e.g., Pinecone, Weaviate), and RAG architectures for production-grade AI agents. 

• Troubleshoot low-level system issues (API failures, latency bottlenecks, memory leaks) and provide root-cause analysis. 

• Build POCs and MVPs with measurable KPIs (latency, throughput, accuracy, adoption). 

Stakeholder Engagement & Change Management 

• Partners with Transaction Management, Lease Administration, and Consulting teams to map workflows into technical blueprints. 

• Deliver training sessions on AI agent orchestration, prompt engineering, and system integration. 

• Collect post-deployment telemetry (usage logs, error rates, adoption metrics) and iterate solutions accordingly. 

• Communicate architecture decisions, trade-offs, and technical risks to leadership and cross-functional teams. 

Governance & Quality Assurance 

• Ensure compliance with enterprise security standards, data governance policies, and ethical AI guidelines. 

• Document LLD diagrams, sequence flows, API specifications, and deployment playbooks. 

• Monitor solution performance using observability stacks (Grafana, Prometheus). 

• Implement automated testing frameworks (unit, integration, regression) for AI workflows. 

Required Qualifications 

Technical Skills 

• 10+ years in product management, technical solution architecture, AI/ML engineering. 

• Prior experience as Data Scientist or AI/ML developer, with hands-on exposure to automation platforms and enterprise AI deployment. 

• Strong background in solution architecture for GenAI systems, including multi-agent orchestration. 

• Hands-on expertise with PyTorch, TensorFlow, LangGraph, LlamaIndex, Hugging Face. 

• Proficiency in Python, JavaScript, or equivalent programming languages. 

• Deep understanding of APIs, microservices, system integrations, and event-driven data workflows. 

• Cloud-native experience with AWS, Azure, or GCP, including IAM, Kubernetes, and serverless architectures. 

Business & Domain Knowledge 

• Understanding of commercial real estate operations (Transaction Management, Lease Administration). 

• Ability to map complex workflows into automation opportunities. 

• Strong grasp of change management principles and enterprise adoption strategies. 

Core Competencies 

• Ability to engage technical and non-technical audiences with architecture-first clarity. 

• Hands-on problem-solving mindset with deep technical troubleshooting. 

• Comfort in ambiguous, high-scale environments with evolving AI technologies. 

• Strong project management across multiple technical streams. 

• Collaborative team player with independent technical ownership. 

Preferred Qualifications 

• Experience with SAFe Agile/Scrum methodologies and technical product frameworks. 

• Background in PropTech, enterprise SaaS, or AI-driven real estate solutions. 

• Hands-on experience with AI agents, MCP, LLM orchestration, and generative AI applications. 

• Prior client-facing consulting experience with technical solution delivery. 

• Certifications in Product Management (CSPO, CPO) or cloud/AI technical certifications. 

Success Metrics 

• AI solutions deployed with quantifiable business impact (time savings, accuracy, cost reduction). 

• High user adoption rates validated by telemetry and feedback loops. 

• Strong technical partnerships with engineering and business stakeholders. 

• Clear roadmap alignment with enterprise strategic priorities. 

• Scalable solutions across geographies and client accounts.