bengaluru, India
4 days ago
Engineering Program Manager

Company Description

Bosch Global Software Technologies Private Limited is a 100% owned subsidiary of Robert Bosch GmbH, one of the world's leading global supplier of technology and services, offering end-to-end Engineering, IT and Business Solutions. With over 27,000+ associates, it’s the largest software development center of Bosch, outside Germany, indicating that it is the Technology Powerhouse of Bosch in India with a global footprint and presence in the US, Europe and the Asia Pacific region.

Job Description

Roles & Responsibilities :
Managerial & Strategic

Lead and mentor a multidisciplinary AI engineering team (ML engineers, data scientists, AI agents specialists, etc.).

Translate business strategies into product/technology roadmaps and delivery plans.

Work closely with Enterprise Architecture, Product, and Leadership to ensure strategic alignment and platform-scale feasibility.

Manage project budgets, resources, timelines, and vendor relationships.

Define OKRs, KPIs, and value outcomes for AI-driven initiatives.

Ensure knowledge sharing, documentation, and operational playbooks for AI platforms and agentic solutions.

Technical & Delivery Execution

Plan and oversee the development lifecycle of agentic AI systems, including data pipelines, LLM/agent orchestration, evaluation frameworks, and integration layers.

Coordinate with the Enterprise Architect to ensure solution integrity, scalability, compliance, and interoperability with enterprise systems.

Drive the execution of proof-of-concepts, prototypes, and pilot deployments, transitioning them to production environments.

Facilitate architectural discussions related to:

LLM selection, fine-tuning, and observability

Agentic workflow frameworks and orchestration tools

API integrations, microservices, and system interoperability

Data security, access governance, and MLOps

Oversee QA, testing, benchmarking, and performance evaluation of AI models and agent workflows.

Business & Stakeholder Management

Act as the primary liaison among technical teams, business stakeholders, and external partners.

Gather and prioritize requirements from business units and stakeholders.

Convert business requirements into technical specifications, acceptance criteria, and success metrics.

Present project progress, risk posture, and performance insights to executives.

Drive change management, adoption strategies, training, and enablement for AI-enabled workflows.

 
 

Qualifications

Experience & Qualifications

5+ years of experience in technology program/project management, product delivery, or solution ownership roles.

Experience working on AI/ML, data platforms, enterprise SaaS, or agentic/automation technologies.

Background working with cross-functional engineering, architecture, and business teams in large, complex organizations.

Demonstrated success delivering enterprise technology initiatives from inception through production deployment.

Strong business acumen to connect AI investments with ROI, operational efficiency, or revenue impact.

Additional Information

Required Skills & Competencies

 

Business & Leadership

Strong strategic thinking with ability to articulate business value of AI initiatives.

Excellent stakeholder management, communication, and presentation skills.

Proven ability to manage cross-functional teams in fast-evolving technical environments.

Skilled in Agile methodologies (Scrum, Kanban) and modern delivery management practices.

Technical Knowledge (Manager-Level)

Good understanding of:

Machine Learning and LLM concepts

AI agentic architectures and tool orchestration frameworks

Data pipeline architecture, storage, and governance

APIs, microservices, and cloud-native solution patterns

DevOps/MLOps fundamentals (CI/CD, model lifecycle management)

Ability to evaluate technical tradeoffs and advise on solution approaches (without needing to build them directly).

 

Project Management

Strong experience with planning, scheduling, sprint and backlog management, and risk mitigation.

Experience integrating external vendors, platform partners, and third-party AI tools.

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