Required Experience, minimum: 10 years

Required Experience, maximum: 12 years

Minimum Qualification: BCA

- B.Tech/B.E

Role

Lead Value Flow Engineer (Expert)

Visit our website bmwtechworks.in to know more.

About the UNIT/ Unit Overview

AIRE (AI-native Requirements Engineering) is a new BMW Group tool for managing vehicle requirements, the descriptions of what a car and its software must do. It keeps the full history of every requirement, shows how requirements are linked to each other and to tests, and shows what is affected when something changes. It helps teams meet automotive standards such as Automotive SPICE and ISO 26262. AIRE is built for AI agents first and a user interface later, and the team uses AI agents to help build it. In this role you build the core storage of AIRE, which keeps every version of every requirement and lets teams look back in time, branch and merge.

Location

Pune or Bangalore

Experience

Number of openings

1

What awaits you/ Job Profile

- Own the AIRE product vision, goals, non-goals and roadmap. Protect the agreed scope (for example read-only domain behaviour, no UI and no write-back to Codebeamer in the proof of concept) and steer explicit scope changes through the sponsor.

- Own and prioritise the backlog. Ensure every item is agent-ready: it has clear acceptance criteria, traces to the L0/L1/L2 requirements, and has a definition of done that includes tests, AI evaluations, audit evidence and required human approvals.

- Facilitate delivery in a deliberately lean, AI-native team. Remove impediments such as data approvals, Codebeamer access, IAM onboarding and masking clearance, and keep alignment overhead minimal.

- Partner with the Lead Software & Systems Architect and the Lead Agentic Engineering & AI Platform Engineer to balance value, feasibility, quality, security, operability and cost. Architecture decisions remain with the architect, and harness and AI-platform decisions remain with the agentic engineering lead.

- Organise discovery and domain validation with the pilot domain department. Plan and steer the read-only shadow run, and consolidate measurements into an evidence-based Go/No-Go recommendation for the sponsor.

- Define and track outcome, flow and AI-native delivery metrics. Examples include acceptance rate of agent-generated changes, rework rate, evaluation pass rate,



defect escape rate and cost per delivered change. Use the findings to improve both the product and the delivery process.

- Own the product-level approval gates in the delivery process, such as release of increments, acceptance of measurement reports and approval of expensive load-test runs. Enforce separation of duties between requesters and approvers.

- Run reviews and demonstrations through the example agent, CLI and TRLC workflows instead of UI mock-ups, and keep stakeholders informed about progress, evidence and risks.

- Prepare the follow-on engagement, including productisation, the later UI phase, team scaling and the operating model, based on the evidence produced.

- Plan the path from the PoC to first production in 2028 Q3, including migration scenarios, cut-over planning, go-live readiness and hypercare.

- Plan the staffing and handover from the internal team to the new DevOps team that owns AIRE from the idea to operations.

What should you bring along

- Degree in Computer Science, Information Systems, Engineering, Business Informatics, or equivalent relevant experience.

- Minimum of eight years of relevant experience in software product development or delivery, including at least three years as a product owner, product manager or value-stream lead for technical platforms.

- Demonstrated track record of delivering complex software products with cross-functional teams and measurable outcomes, ideally in regulated or engineering-heavy domains.

- Proven ability to lead through influence, manage senior stakeholders and make evidence-based product decisions, without requiring prior line-management experience.

Must have technical skill

- Proven product ownership or value-stream leadership for complex enterprise, engineering or developer platforms from discovery through production, beyond feature-factory delivery.

- Ability to translate stakeholder goals into measurable outcomes, hypotheses and success criteria. Examples include weighted benchmark matrices, service-level objectives,



Go/No-Go criteria and adoption metrics. Protect scope through explicit goals and non-goals.

- Practical experience leading AI-native delivery: specification-driven development, agent-generated work products, bounded implementation and verification loops, human approval gates, and measuring flow when agents produce most of the code.

- Ability to write and curate machine-readable backlog items and specifications that agents can execute and humans can verify. These include user stories, acceptance criteria, BDD scenarios and traceable L0–L2 requirements.

- Strong flow and backlog management with the Agile Working Model, Kanban or Scrum, including WIP limits, flow metrics (lead time, throughput, flow efficiency) and dependency management across domain, platform and governance units.

- Stakeholder and expectation management with sponsors, domain departments, system owners of legacy tools, architecture, and data protection and information security functions, including timely escalation of blocking approvals.

- Sound understanding of the automotive requirements engineering and ALM landscape (for example Codebeamer, IBM DOORS, Polarion, ReqIF) and of the regulatory drivers Automotive SPICE and ISO 26262.

- Structured management of risks, assumptions and dependencies, including data approvals, masking, IP and NDA constraints, and the availability of interfaces to legacy systems.

- Excellent communication, facilitation and negotiation skills, with the ability to keep coordination overhead low so that AI-driven delivery speed is not lost in alignment meetings.

Positive to have technical skills

- Prior experience with the BMW Agile Working Model, BMW BASE (BMW Agentic Software Engineering) and BMW-specific governance and release processes.

- Knowledge of product line engineering, feature models and variant management in automotive development.

- Experience with requirements-as-code and docs-as-code approaches such as TRLC (Treat Requirements Like Code), Git-based reviews and CI-driven validation.

- Experience introducing a successor solution alongside a leading legacy system, including shadow runs, co-existence and migration decision-making.

- Understanding of AI operating cost (LLM token and inference cost), FinOps and AI value measurement.

- German language skills for working with domain departments and source material.

📌 Lead Value Flow Engineer (AIRE) (Pune)
🏢 BMW TechWorks India
📍 Pune