Job Description

The Bosch Group is a leading global supplier of technology and services. Since the beginning of 2013, its operations have been divided into four business sectors: Automotive Technology, Industrial Technology, Consumer Goods, and Energy and Building Technology.

The Bosch Group comprises Robert Bosch GmbH and its roughly 360 subsidiaries and regional companies in some 50 countries. If its sales and service partners are included, then Bosch is represented in roughly 150 countries. This worldwide development, manufacturing, and sales network is the foundation for further growth.

Bosch Global Software Technologies Company Limited (BGSV) is 100% owned subsidiary of Robert Bosch GmbH - one of the world’s leading global suppliers of technology and services, offering end-to-end Engineering, IT, and Business Solutions.

Starting its operation from 2010 at Etown 2 in HCMC, BGSV is the first software development center of Bosch in Southeast Asia. BGSV nowadays have over 4,000 associates, with a global footprint and presence in the US, Europe, and the Asia Pacific region.

With our unique ability to offer end-to-end solutions that connect sensors, software, and services, we enable businesses to move from the traditional to digital or improve businesses by introducing a digital element in their products and processes.

AI Global Product & Service Transformation | Serving 500,000+ users worldwide

Are you ready to build a native‑AI product at global scale?

This isn’t a “POC” or a short‑term experiment. We are building a long‑term, strategic Agentic AI architecture to transform an enterprise workflow platform used by 500k+ users globally into an AI‑first product—one that can understand requirements, generate workflow applications (and code), validate quality, and continuously improve accuracy and user outcomes

We’ve already completed the foundation for two AI agents in our AI architecture. Now we’re scaling from “agents exist” to agents that are accurate, reliable, secure, and production‑ready at enterprise scale If you want your work to matter—and want a rare chance to ship AI into real operations across a major corporation—this role is for you.

🚀 Why this role is a career‑defining move

1) Build the future—not just models.

You will help create Agentic AI that can generate workflow applications from business requirements or legacy source code, including deployment artifacts and modernization outputs.

2) Massive real‑world impact.

Your engineering decisions will affect hundreds of thousands of users—with measurable outcomes: cycle time, quality, compliance, and platform cost reduction.

3) Hard problems, serious ownership.

This role demands more than AI knowledge. You’ll need strong full‑stack engineering maturity to build robust systems around LLMs: orchestration, evaluation, observability, security, and scalable delivery.

4) Long‑term mission with real investment.

This is a multi‑year transformation with committed funding and roadmap. We’re looking for an engineer who wants deep ownership, long‑term growth, and meaningful achievements—not quick wins.

🎯 Your mission

Help us evolve our AI‑Driven Workflow Platform into a native AI Product & Service by building an Agentic AI architecture that can:

• Turn legacy knowledge (data, logs, procedures, docs) into usable intelligence
• Generate workflow apps (and code) from requirements or existing legacy assets
• Improve accuracy through evaluation, feedback loops, and continuous learning
• Operate safely at enterprise scale with governance, security, and reliability

🧩 What you will do (Responsibilities)

Turn Legacy into Leverage

• Deep‑dive into legacy environments—SQL procedures, logs, documentation, and siloed datasets
• Design pipelines that extract structured intelligence from historical systems
• Convert fragmented data into high‑ quality, AI‑ ready datasets

Build AI at the Core of the Product

• Design, develop, and deploy production‑grade AI capabilities for the AI‑Driven Workflow Platform
• Enable intelligent workflow routing, natural‑language interfaces (LLMs), predictive insights, and anomaly detection

Engineer Signals That Matter

• Lead feature engineering focused on workflow optimization
• Identify bottlenecks, predict failures, and surface insights that directly improve operational efficiency

Own Global‑Scale AI Systems

• Drive MLOps strategy across regions
• Own the full AI lifecycle: training, evaluation, deployment, monitoring, and optimization
• Optimize for accuracy, latency, cost, scalability, and maintainability

Modernize with Generative AI

• Apply GenAI and LLMs to reverse‑engineer and modernize legacy codebases
• Transform outdated logic into clean, documented, cloud‑native services

Lead and Influence

• Mentor engineers and raise AI engineering standards
• Work closely with Product teams to translate complex processes into intuitive, AI‑powered user experiences

🛠️ Tech areas you’ll likely work with

(We’re flexible on exact tools if you can deliver outcomes.)

• LLMs / GenAI: prompt engineering, RAG, fine‑tuning (where needed), structured generation, tool‑calling
• Agent frameworks: LangChain/LangGraph or equivalents
• Backend: Python (must), microservices, REST/gRPC, event‑driven patterns
• Data/Knowledge: ETL/ELT, vector DBs, graph DBs, search, indexing, document pipelines
• MLOps/LLMOps: MLflow/Airflow or equivalents, CI/CD, eval pipelines
• Infra: Docker/Kubernetes, cloud (Azure/AWS/GCP), monitoring/telemetry

Qualifications

Must‑Have

• 7+ years in software or data engineering, including 4+ years deploying AI/ML systems in large‑scale production
• Expert‑level Python
• Hands‑on experience with modern LLM workflows fine‑tuning, RAG, evaluation, agent orchestration (LangChain, LangGraph, or equivalent)
• Strong full‑stack engineering background with end‑to‑end system ownership
• Deep experience in data engineering ETL pipelines, NoSQL / Graph databases, large‑scale processing (e.g., Spark)
• High tolerance for messy enterprise data and complex legacy environments
• Practical experience with MLOps (MLflow, Airflow), containers (Docker, Kubernetes), and cloud platforms (AWS, Azure, or GCP)

Nice‑to‑Have

• Experience modernizing legacy systems or extracting intelligence from older architectures
• Background in Low‑Code / No‑Code platforms or business process automation
• Knowledge of performance and cost optimization (model compilation, quantization, inference optimization)

🌟 What success looks like (first 6–12 months)

• Deliver production improvements that increase accuracy and reduce rework in our AI agents
• Implement measurable evaluation and observability (dashboards + quality gates)
• Ship at least one major capability: e.g., application generation from requirements, or legacy code → modern artifact generation
• Establish patterns for safe enterprise deployment: guardrails, audits, and stable operations

💙 What you’ll gain

• A rare chance to build real Agentic AI inside a global product used at scale
• Deep experience across AI + full‑stack engineering + enterprise delivery
• High ownership and visibility: your work materially impacts platform direction and business outcomes
• A long‑term journey where you can grow into a principal/architect path as the program scales

✍️ Show us your impact (300 words max)

In your application, please answer:

“Describe the most complex or impactful AI system you shipped. What was the core problem, what was your role, and what outcome did it achieve?”

If you’ve worked on agentic systems, code generation, application generation, or legacy modernization, highlight it.

Additional Information

• Private Health Insurance (Generali) Covered by company
• Personal Accident Insurance Covered by company
• 13-month Salary Bonus Guaranteed upon contract completion. ( Payment timing: Included in the final payroll of labor contract)
• 12 days annual leave