Senior, Principal Technical Solution Owner/ Product Manager (AI & Data Platforms

What You’ll Do:

• Architect Product Strategy for Technical Platforms:
• Define product strategy for AI platforms, data infrastructure, and enterprise-scale data migration initiatives.
• Lead technical product discovery – evaluating emerging technologies (GenAI, Agentic AI, vector databases, streaming architectures) and assessing fit for client use cases.
• Design solution architectures in collaboration with data architects and engineers, making build-vs-buy decisions and technology stack selections.
• Develop technical roadmaps balancing innovation, scalability, security, and time-to-value.
• Drive AI/ML Product Development:
• Own end-to-end product lifecycle for GenAI applications leveraging LLMs, RAG architectures, Agentic frameworks, and multi-modal AI systems.
• Translate business requirements into technical specifications, API contracts, data schemas, and system integration patterns.
• Guide model selection, evaluation criteria, and deployment strategies for ML models in production environments.
• Champion MLOps practices including model versioning, monitoring, performance tracking, and continuous improvement loops.
• Manage Complex Data Platform Initiatives:
• Lead product planning for data lake/lakehouse implementations, warehouse modernizations, and cloud data platform migrations.
• Define data product requirements including ingestion pipelines, transformation logic, data quality rules, governance policies, and access patterns.
• Oversee integration of multiple data domains, ensuring interoperability, data lineage, and metadata management.
• Partner with data engineering teams on performance optimization, cost management, and scalability planning.
• Execute Through Agile Delivery:
• Facilitate Agile ceremonies and maintain well-groomed backlogs with properly sized, technically detailed Features and Epic level stories.
• Work closely with engineering teams to decompose complex features into incremental releases with clear technical dependencies.
• Define sprint goals aligned with quarterly objectives and long-term product vision.
• Balance technical debt management with feature delivery, advocating for enablers and architectural improvements.
• Enable Technical Decision-Making:
• Conduct technical due diligence, proofs-of-concept, and spike solutions to validate approaches before full investment.
• Analyze trade-offs between competing technical solutions considering performance, cost, maintainability, and developer experience.
• Document technical decisions, architectural decision records (ADRs), and design patterns for knowledge sharing.
• Communicate technical strategies and recommendations to executive stakeholders with clarity and conviction.

What You Bring:

• Required Qualifications:
• Bachelor's degree in Technology or Business related field (Master's preferred).
• 5-7+ years of experience in technical product management, solutions architecture, or software engineering.
• 5+ years in product management roles with demonstrated end-to-end product ownership.
• 3-5+ years of experience with AI/ML products, Generative AI, or data platform development.
• 3-5+ years working in Agile/Scrum environments with strong command of Agile methodologies and ceremonies.
• Deep understanding of cloud architectures (AWS, Azure, GCP) and modern data stack technologies.
• Technical Expertise:
• AI/GenAI: LLM integration, prompt engineering, RAG architectures, fine-tuning, Agentic AI frameworks (LangChain, LlamaIndex, AutoGen).
• Data Engineering: ETL/ELT patterns, data modeling, Snowflake, Databricks, dbt, Airflow, Kafka/streaming architectures.
• Cloud Platforms: AWS (SageMaker, Bedrock, Glue), Azure (OpenAI Service, Synapse), GCP (Vertex AI, BigQuery).
• MLOps: Model deployment, monitoring, versioning, CI/CD for ML, feature stores, experiment tracking.
• Data Migration: Assessment methodologies, migration patterns, data validation, cutover strategies.
• Development Practices: API design, microservices, containerization (Docker, Kubernetes), CI/CD pipelines.
• Core Competencies:
• Solution design and technical architecture capabilities.
• Requirements translation from business needs to technical specifications.
• Strong analytical thinking and problem-solving in complex technical domains.
• Exceptional stakeholder management across technical and non-technical audiences.
• Clear technical communication—documenting complex systems and presenting architectural decisions.
• Risk identification, dependency mapping, and mitigation planning.
• Preferred Qualifications:
• Prior software development or data engineering experience (3+ years).
• Background in consulting or professional services delivering client solutions.
• Certifications: AWS Solutions Architect, Azure Data Engineer, GCP Professional Data Engineer, Certified Scrum Product Owner.
• Personal Attributes:
• Insatiable curiosity about emerging technologies and hands-on experimentation mindset.
• High attention to detail with quality focus and commitment to technical excellence.
• Collaborative team player who thrives in cross-functional environments.
• Adaptable and comfortable navigating ambiguity in fast-paced consulting contexts.
• Passion for mentoring engineers and elevating technical practices.

Why Join Us:

• Lead top-tier engineering teams and cutting-edge agentic AI systems, enterprise AI platforms.
• Shape how enterprises adopt AI — from strategy to architecture to delivery.
• Grow within a team building modern AI-delivery practices, tools, and frameworks.
• Remote-friendly culture with strong engineering, data, and consulting partnerships.