GenAI and Data Architect

Company Overview

• Mid-Sized Pioneering Product Engineering and Digital Transformation Company
• Domains: Semiconductor, Automotive, industrial, Consumer Electronics, Enterprise Devices, Telecom, Transportation
• Customers: OEMs, Tier1s
• Successfully service Fortune 500 Companies
• Customer Geographies: U.S., Canada, Nordics, Germany, Japan

Job Description

Role: GenAI and Data Architect

Role Overview: We are seeking a proven Architect and Technical Leader with deep expertise in Agentic AI, GenAI, Data Architecture, And Cloud Technologies. This leader will serve as a

• Presales Architect Leader, Architecting and Consultatively Selling transformative solutions to Enterprise and ISV Customers in the US, Europe and Japan.
• Technically Guide Delivery Team in Technical Execution

The leader will play a pivotal role in shaping our organization’s strategic growth in NextGen technologies.

Reporting Manager: Vice President

Location: Whitefield, Bengaluru

Key Responsibilities Serve as a Lead Presales / Delivery/Solution Architect for high-value prospects in US, Europe and Japan. Primary focus will be on:

• Presales Responsibilities:

• Focus will be on new customer acquisition, winning long-term strategic customers, and existing large accounts
• Lead technical discussions with prospective and existing customers to articulate our offerings and value proposition, present case studies and understand / evaluate customer’s Business-Technology Goals and Requirements
• Qualify prospects by understanding their industry, products or services, their existing and future revenue streams and their predominant business-Technology needs and aspirations
• Support the sales team in winning deals by synthesizing together industry leading solutions in collaboration with SMEs

Architect technical solutions for customers:

• Architect comprehensive Agentic AI and Generative AI solutions from concept to deployment that align with organizational objectives and support horizontal scaling.
• Drive architectural decisions for GenAI platforms, encompassing model selection, infrastructure planning, and system integration patterns.
• Lead data architecture modernization initiatives for both Enterprise and ISV Platforms
• Define target-state data architectures and migration roadmaps for AI Deployment At Scale

• Own End-to-End responsibility for Proposals– from Sales Discussions to successfully defending technical Proposals
• Support the Sales team in winning the deals by synthesizing together solutions in collaboration with SMEs, that addresses client requirements
• Develop persuasive technical collateral and deliver targeted messaging to stimulate and engage prospects while stretching the imagination to visualize the Art of Possible
• Develop proactive whitepapers, POC concepts, proposals, and respond to RFQs with complete responsibility for bid management
• Focus will be on new customer acquisition and winning long-term strategic deals
• Serve as a custodian of Go to Market (GTM) decks and offerings
• Be on top of latest technologies and upcoming trends and seamlessly articulate the value propositions and payoffs to delivery teams, prospects and existing customers

2.Technical Guidance to Delivery Team Responsibilities:

• Provide technical advisory to delivery team across multiple concurrent projects, balancing hands-on problem-solving with strategic guidance
• Define and maintain architectural standards, guidelines, and best practices for generative AI deployments across the project portfolio
• Oversee security, compliance, cost efficiency, and reliability of production AI systems
• Facilitate technical proof-of-concepts, and spike solutions to validate architectural approaches and de-risk complex implementations.
• Provide hands-on technical advisory to engineering teams throughout project delivery lifecycle, including architecture reviews, code reviews, and troubleshooting complex technical challenges.
• Conduct design reviews and technical checkpoints to ensure adherence to architectural principles, performance requirements, and quality standards.
• Guide engineering teams through technical decision-making processes, risk mitigation strategies, and resolution of technical blockers to maintain project momentum.
• Unblock Delivery Team through root cause analysis, performance optimization, and architectural refactoring recommendations during critical delivery phases.
• Mentoring GenAI engineers and Data Team Leads
• Build, sustain and maintain long term relationship with key and strategic customers

Experience And Skill Requirements:

Education: B.Tech / B.E. in Computer Science / IT / Electronics. Master’s Degree (Preferred)

Experience:

• 12–15+ Years Total Experience
• 4+ Years in Presales Interfacing with US / Europe / Japan Customers
• 5+ Years Hands-On Experience Architecting Genai, AI/ML, Data Architecture and Cloud Technology Solutions
• Proven Track Record Winning Long-Term Strategic Deals in Agentic AI / Genai / Data / Cloud / Digital Spaces
• Experience Acquiring Blue-Chip Customers and Coaching Sales Teams On Genai/Data Value Communication

Technical Expertise You Will Bring:

Agentic AI

• Knowledge of Agentic AI frameworks (LangGraph, AutoGen, CrewAI, LangChain Agents) and Multi-Agent orchestration patterns
• Experience designing and implementing Agent workflows with tool use, function calling, and reasoning capabilities
• Understanding of Agent Memory Systems, planning strategies, and feedback loops for iterative task execution

GenAI And MLOps Fundamentals

• Deep knowledge of GenAI fundamentals with practical experience with leading GenAI platforms (e.g., Anthropic, Google AI, OpenAI, Azure OpenAI, AWS Bedrock)
• Expertise in prompt engineering and LLM optimization techniques
• Demonstrated success designing and deploying RAG architectures, including vector stores (Pinecone, Weaviate, ChromaDB), embedding strategies, chunking logic, semantic retrieval, and hybrid search
• Experience with MLOps frameworks and platforms (MLflow, Kubeflow, SageMaker, Vertex AI) for model lifecycle management, experiment tracking, and model registry
• Proficiency in model versioning, A/B testing strategies, and canary deployments for AI models in production environments
• Expertise in design patterns, clean architecture principles, and AI-specific testing approaches
• Hands-on experience with data versioning tools (DVC, LakeFS) and feature stores for ML pipeline orchestration
• Familiarity with monitoring and observability tools (e.g., LangSmith, Langfuse) for productionizing AI systems
• Knowledge about CI/CD pipelines, automated testing strategies, and DevOps practices for AI/ML workloads

Data Architecture and Platform Modernization

• Expertise in Master Data Management Solutions and Data Governance frameworks to ensure data consistency, accuracy, and lineage across enterprise systems
• Proficiency in dimensional and relational data modeling techniques (star schema, snowflake schema, data vault) and modern Data Lakehouse architectures (Delta Lake, Iceberg, Hudi)
• Experience implementing data quality frameworks and tools (Deequ, Monte Carlo) with automated data profiling, validation rules, and anomaly detection for AI-ready datasets
• Deep Hands-on experience with Databricks and/or Snowflake Data / AI Platforms
• Deep Hands-on experience with at least one of the following Hyperscaler AI / Data Platforms: Azure, AWS
• Proven track record leading either Enterprise Data Architecture Modernization programs and/or ISV Data Products
• Enterprise Data Modernization: legacy-to-cloud migrations, ETL-to-ELT transformations, and batch-to-streaming architecture transitions
• Modernizing ISV Data Products: Multi-tenancy architectures, SaaS data isolation patterns, API-first design, and embedded analytics capabilities
• Knowledge of Change Data Capture (CDC) tools (Debezium, Fivetran, Striim), real-time streaming architectures (Kafka, Confluent, Pulsar), and event-driven design patterns for modernization efforts
• Expertise in assessing legacy data estate, conducting technical due diligence, and creating phased modernization strategies with minimal business disruption and zero-downtime migration approaches
• Advanced analytical capabilities to assess trade-offs among design options (performance, cost, scalability, maintainability, time-to-market)
• Demonstrated ability to produce architecture documents, technical diagrams, and stakeholder presentations

Attitude And Interpersonal Skills You Will Bring:

• Clear and critical thinking
• Openness / Willingness to Give / Receive Feedback from Customers and Colleagues
• Exceptional Communication / Presentation / Listening
• Entrepreneurial Hunger to Grow New Business
• Aesthetic Sense, Positive / Optimistic Mindset
• Excitement To Build Agentic AI / GenAI / Data Initiatives in High-Growth Environment

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