Technical Product Manager ensuring seamless integrations for Docebo's AI - powered learning platform. Focusing on managing enterprise ecosystem for client success through connector development.
About the role
- Technical Product Manager at ShyftLabs leading complex AI and data initiatives with a focus on data management and orchestration. Collaborating with engineering teams for scalable solutions.
Responsibilities
- Own and drive the end-to-end lifecycle of AI- and data-intensive technical initiatives across multiple products.
- Define and evolve data management strategy, including data modeling standards, pipeline requirements, governance, lineage, and quality frameworks.
- Lead product strategy for agentic systems, including orchestration layers, tool usage patterns, memory/context management, guardrails, and fallback strategies.
- Establish and operationalize evaluation frameworks for AI products (LLM evals, benchmarking, human-in-the-loop review, automated scoring, drift monitoring).
- Partner with engineering to design scalable architectures that support data ingestion, transformation, context retrieval, and multi-agent coordination.
- Translate business objectives into clear technical specifications spanning APIs, data contracts, orchestration logic, and observability requirements.
- Define metrics for success across system performance, data quality, model reliability, latency, cost optimization, and user outcomes.
- Identify and mitigate risks across model behavior, data integrity, security, and compliance.
- Oversee validation processes for AI systems, including regression testing, prompt versioning, evaluation harnesses, and continuous improvement loops.
- Act as a bridge between product, data engineering, ML engineering, and platform teams to ensure technical alignment and delivery excellence.
- Communicate roadmap progress, architectural trade-offs, and performance insights to executive stakeholders with clarity and rigor.
- Foster a culture of accountability, structured experimentation, and high technical standards across teams.
Requirements
- Bachelor’s degree in Computer Science, Information Technology, Engineering, or a related technical field.
- 2–5 years of experience in technical product management, preferably in AI, ML, or data platform environments.
- Strong understanding of data architecture and data management principles, including data modeling, governance, lineage, quality monitoring, and cloud data platforms.
- Demonstrated experience working on AI-powered or agent-based products, including orchestration patterns and evaluation methodologies.
- Familiarity with LLM concepts such as context windows, retrieval augmentation (RAG), prompt orchestration, tool calling, memory management, and guardrails.
- Experience defining and operationalizing evaluation frameworks (offline/online testing, experimentation, quality metrics, performance benchmarking).
- Deep understanding of cloud computing platforms, distributed systems, APIs, and integration patterns.
- Hands-on exposure to Agile methodologies, DevOps practices, and CI/CD pipelines.
- Strong analytical thinking, structured problem-solving, and data-driven decision-making skills.
- Excellent communication and stakeholder management abilities, including executive-level reporting.
Benefits
- Comprehensive Benefits: We cover 100% of health, dental, and vision insurance premiums for you and your dependents which means no out-of-pocket costs. Eligibility starts from day one itself.
- Growth & Learning: Access extensive learning and development resources to keep leveling up your skills.
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