Technical Project Manager

Role overview : The Technical Project Manager (AI, Data & Automation) will lead the end-to-end planning, execution, and delivery of AI-driven data products, reporting dashboards, and automation solutions. This role uniquely blends agile delivery leadership, technical context engineering, and AI solution orchestration — ensuring that LLMs, agents, and data systems work in harmony to drive business impact.

You will collaborate with product owners, data engineers, AI developers, and business stakeholders to ensure dashboards, models, and AI agents are delivered with precision, scalability, and measurable outcomes. Beyond project execution, you will help evolve internal best practices for AI product delivery, including context design, model evaluation, and agent observability.

Key Responsibilities :

Project & Delivery Management

Define, plan, and manage delivery timelines for AI, data, and BI projects (Power BI, Tableau, Datorama, etc.)

Lead sprint planning, UAT cycles, and release management using Agile (Scrum / Kanban) frameworks

Maintain delivery documentation — user stories, acceptance criteria, dependency trackers, and sprint reports

Monitor KPIs such as velocity, sprint burndown, delivery variance, and model deployment readiness

Technical Context & AI Orchestration

Collaborate with data scientists, prompt engineers, and developers to convert business problems into LLM workflows

Build and manage context frameworks, prompt libraries, and retrieval pipelines using LangChain, LlamaIndex, or similar orchestration layers

Track model performance, latency, and response accuracy through LangFuse, Weights & Biases, or PromptLayer for observability and evaluation

Design AI agent architectures that integrate with data systems (SQL, APIs, cloud data stores) and downstream visualization tools

Support technical feasibility assessments, architecture discussions, and proof-of-concept builds for AI agents and copilots

Partner with engineering to implement guardrails, prompt validation, and feedback loops for production-grade AI reliability

Stakeholder & Cross-Functional Alignment

Act as the bridge between business teams (Marketing, PMs, Strategy) and technical delivery squads

Define clear project scopes, delivery milestones, and stakeholder reporting rhythms

Facilitate weekly progress syncs, demo reviews, and cross-team retrospectives

Manage change control, risk tracking, and communication for multi-project programs

Quality, UAT & Continuous Optimization

Design and coordinate UAT plans for dashboards, data pipelines, and AI agents

Validate AI performance against qualitative (accuracy, relevance, consistency) and quantitative (latency, token cost, precision) benchmarks

Capture feedback loops for fine-tuning models, retraining datasets, or updating prompt templates

Ensure that delivery documentation and dashboards meet expected usability and performance standards

Strategic Enablement & Practice Building

Define internal standards for AI project delivery, including experimentation logs, evaluation metrics, and documentation templates

Contribute to developing multi-client AI reporting frameworks and automation playbooks

Benchmark AI orchestration tools (LangChain, Haystack, Dust, OpenDevin) and delivery processes for continuous improvement

Partner with leadership on roadmap prioritization, team resourcing, and delivery governance

Mentor junior PMs and BSAs to operate effectively within AI + Data delivery contexts

Required Skills & Experience

6 to 10 years of relevant experience

Proven understanding of data pipelines, APIs, and BI tools (Power BI, Datorama, Tableau)

Working familiarity with AI / LLM toolchains — LangChain, LangFuse, LlamaIndex, OpenAI, Anthropic, or Azure OpenAI

Understanding of prompt engineering, context window optimization, and RAG (Retrieval-Augmented Generation) design

Experience coordinating with teams using Python, FastAPI, SQL, and cloud platforms (AWS / Azure)

Exposure to model monitoring, prompt versioning, and evaluation pipelines

Ability to interpret structured / unstructured data and manage integrations between AI and data visualization layers

Strong experience leading AI, data, or analytics product delivery using Agile / Scrum

Skilled in backlog management, sprint planning, and multi-project coordination.

Proficiency with PM tools — Jira, ClickUp, Monday.com, Confluence, or similar.

Excellent skills in cross-functional communication, requirements clarity, and delivery

Certifications : PMP or Prince II

Prior experience delivering AI agents, chatbots, copilots, or automation systems

Exposure to AI evaluation pipelines (LangFuse, Traceloop, Arize) and prompt management tools

Experience in marketing analytics, optimization platforms, or enterprise data systems