Product Manager - Amazon (Data Modernization)
TEK Systems- Location
- United States
- Workplace
- —
- Employment
- —
- Salary
- USD 128,000–192,000/yr
Posted yesterday
Overview
Before applying for a TGS role, internal employees must discuss their interest with their current manager.
Please share this direct link with your manager so they can submit their approval. Your application cannot move forward until the form is completed.
TEKsystems Global Services (TGS) is seeking a Product Manager to lead enterprise Data Operations initiatives and the delivery of multi-modal data annotation, prompt/context engineering, model evaluation and Agentic AI solutions. This role blends product ownership with product operations execution, enabling clients to operationalize their data for AI models and build AI agents while meeting enterprise standards for security, governance, scalability, and compliance.
You will define and drive product strategy while orchestrating end‑to‑end delivery of DataOps‑enabled AI platforms and agentic workflows that leverage AI frameworks.
Responsibilities
Key Responsibilities
Product Management & Data Operations
- Own the product vision, roadmap, and backlog for data and agentic AI capabilities across enterprise client engagements.
- Translate business needs into outcome‑driven product/service requirements and architecture.
- Define success metrics tied to data reliability/quality, AI agent effectiveness, automation value, and operational efficiency.
- Develop PRDs, user stories, and acceptance criteria with a strong focus on operability, reuse, and scalability.
- Lead cross‑functional delivery across diverse team of data engineering, ML engineering, platform, security, and client stakeholders.
- Plan and execute complex programs spanning DataOps, MLOps, and Agentic AI workflows using Agile delivery methods and AI tools.
- Manage dependencies, risks, and timelines across multiple workstreams and client environments.
- Establish delivery governance including design reviews, readiness checks, operational handoffs, and post‑launch validation.
- Drive implementation and modernization of enterprise DataOps capabilities, including:
- Data ingestion, transformation, and orchestration
- Data modeling, metadata management, and lineage
- Data quality frameworks and observability
- Partner with architects to ensure data tooling is production‑ready, secure, and well‑governed.
- Define and track data SLAs, quality thresholds, and operational metrics in alignment with business use cases.
Agentic AI Solutions
- Lead productization and delivery of Agentic AI systems for example:
- Agent orchestration frameworks (e.g., LangGraph, AutoGen‑OSS, CrewAI, custom orchestration layers)
- Retrieval‑Augmented Generation (RAG) using open vector stores and search engines
- Tool‑using agents that integrate with enterprise APIs, data platforms, and workflow systems
- Multi‑agent workflows for task decomposition, reasoning, validation, and escalation
- Ensure implementations include:
- Prompt and workflow versioning
- Evaluation frameworks and benchmark testing
- Human‑in‑the‑loop controls and fallback mechanisms
- Observability, logging, and traceability
- Balance accuracy, latency, cost, reliability, and safety through iterative experimentation and data‑driven tuning.
Governance, Risk, and Compliance
- Partner with security, legal, and compliance teams to ensure AI agents behave predictably and are in alignment.
- Define controls for PII handling, model access, prompt data retention, and auditability.
- Ensure solutions meet enterprise change management and incident response standards.
Stakeholder Leadership
- Serve as a trusted partner to client product delivery leaders and sales executives.
- Communicate trade‑offs, progress, risks, and value realization clearly and concisely.
- Influence without authority across client and internal delivery ecosystems
Qualifications
Required Qualifications
- Bachelor’s degree in Computer Science, Information Systems, Data/Analytics, or equivalent experience.
- 7–10 years of experience across Product Management and / or Product Operations.
- Proven experience delivering enterprise DataOps platforms, quality data sets and/or AI/ML systems into production.
- Practical experience with AI concepts and frameworks:
- RAG pipelines, embeddings, vector databases
- Agent orchestration and workflow graphs
- Tool/function calling using open APIs
- Experience authoring PRDs, roadmaps, program plans, and executive readouts.
- Strong communication and stakeholder‑management skills in enterprise environments.
- Background in consulting or client‑facing delivery environments such as Sales Support.
Preferred Qualifications
- Advanced degree a plus.
- Experience delivering AI solutions in regulated or compliance‑heavy industries.
- Familiarity with LLM hosting and deployment patterns (self‑hosted or cloud‑agnostic).
- Exposure to LLMOps and MLOps using open tooling (model versioning, evals, CI/CD).
- Experience designing reference architectures or accelerators for reuse across clients.
- Strong hands‑on understanding of data tooling, including:
- Orchestration (e.g., Airflow)
- Transformation and modeling (e.g., dbt)
- Data quality and validation (e.g., Great Expectations)
- Metadata and lineage (e.g., OpenLineage)
Expectations
- Operates independently on ambiguous and complex problem spaces.
- Makes high‑quality architectural and product trade‑offs grounded in data and delivery realities.
- Drives measurable business outcomes, not just feature completion.
- Elevates team and organizational maturity across product, program, and AI delivery practices.
Representative Technology Areas
- Agent Frameworks: LangGraph, AutoGen (OSS), CrewAI, custom agent orchestration
- Data Platforms: Open table formats, Spark‑based engines, open metadata catalogs
- Vector Search: pgvector, FAISS, OpenSearch, Weaviate (OSS)
- Observability & Quality: Open telemetry, open eval frameworks, open data quality tools
- Workflow & Orchestration: Airflow, Kubernetes‑native schedulers
***Posting Close Date: 10/1/2026***
This includes receiving your manager approval form.
We reserve the right to pay above or below the posted wage based on factors unrelated to sex, race, or any other protected classification.
- US Salary range: $128,000-$192,000 Potential bonus up to: $20,000
Compensation will be determined based on a variety of factors which may include, but are not limited to, education, experience, skills, and geographic location. As an internal Allegis Employee exploring roles within TEKsystems Global Services, hiring eligibility and maintaining existing ancillary benefits are subject to change with transfer from one role to another. Please reach out to Talent Mobility for specific questions: TGS_Talent_Ops@teksystems.com.
Eligibility requirements apply to some benefits and may depend on your job classification and length of employment. Benefits are subject to change and may be subject to specific elections, plan, or program terms. If eligible, the benefits available for this temporary role may include the following:
- Medical, dental & vision
- Critical Illness, Accident, and Hospital
- 401(k) Retirement Plan – Pre-tax and Roth post-tax contributions available
- Life Insurance (Voluntary Life & AD&D for the employee and dependents)
- Short and long-term disability
- Health Spending Account (HSA)
- Transportation benefits
- Employee Assistance Program
- Time Off/Leave (PTO, Vacation or Sick Leave)
- https://www.teksystems.com/en/careers/benefits
Skills
- Machine Learning
- MLOps
- LangGraph
- AutoGen
- CrewAI
- Retrieval-Augmented Generation
- Embeddings
- Vector Databases
- LLM
- LLMOps
- Airflow
- dbt
- Great Expectations
- Spark
- pgvector
- FAISS
- OpenSearch
- Weaviate
- OpenTelemetry
- Kubernetes
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