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

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

The leader will play a pivotal role in shaping our organizations 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:

1. 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 customers 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:

1. Architect comprehensive Agentic AI and Generative AI solutions from concept to deployment that align with organizational objectives and support horizontal scaling.
2. Drive architectural decisions for GenAI platforms, encompassing model selection, infrastructure planning, and system integration patterns.
3. Lead data architecture modernization initiatives for both Enterprise and ISV Platforms
4. 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. Masters Degree (Preferred)

Experience:

• 1215+ 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