From Bosch’s careers page.
Company Description
The Bosch Group is a leading global supplier of technology and services. Its operations are divided into four business sectors: Mobility, Industrial Technology, Consumer Goods, and Energy and Building Technology. With technology that is “Invented for life,” Bosch wants to help improve quality of life and conserve natural resources.
The Bosch Group comprises Robert Bosch GmbH and its roughly 490 subsidiary and regional companies in over 60 countries. Including sales and service partners, Bosch’s global manufacturing, engineering, and sales network covers nearly every country in the world. Bosch’s innovative strength is key to the company’s further development.
Bosch Global Software Technologies Company Limited (BGSV) is 100% owned subsidiary of Robert Bosch GmbH, 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.
BGSV currently operates from three offices located at the following addresses:
1. Etown Building – 364 Cong Hoa Street, Ward 13, Tan Binh District, Ho Chi Minh City, Vietnam
2. OfficeHaus Building – 32 Tan Thang Street, Son Ky Ward, Tan Phu District, Ho Chi Minh City, Vietnam
3. Capital Place Building – 29 Lieu Giai Street, Ngoc Khanh Ward, Ba Dinh District, Hanoi, Vietnam
Job Description
- Architect agentic systems — plan, memory, tool use, multi-agent delegation, evaluation loops, guardrails. Pick the right abstraction for the problem, not the one on the hype curve.
- Push model capability into production. Design prompt and context strategies, tool interfaces, retrieval and reranking, structured output, streaming, and evaluation — across text and multimodal inputs (vision, documents, audio).
- Own the evaluation story. Build offline eval sets, online LLM-as-judge loops, regression harnesses. Know the difference between a metric that moves your users and a metric that moves only your dashboard.
- Squeeze the system. Prompt caching, batching, speculative decoding, model routing, token budget management, latency targets. Know your P50/P99 and why they look the way they do.
- Contribute upstream. Read SDK source when docs are thin, open PRs against open-source agent frameworks, write crisp bug reports when a vendor's orchestration service returns a weird 500.
- Mentor and set the bar. Your design reviews, code reviews and technical writing shape how the rest of the team thinks about agents.
Qualifications
- Bachelor’s degree in Artificial Intelligence, Computer Science, or a related field.
- 0-3 years of experience as an AI/AI Agent Engineer.
- Solid ML fundamentals. You can explain transformers — attention, positional encoding, KV cache, tokenisation, sampling — without hand-waving. You've read at least a few core papers in full, not just the abstracts.
- Deep LLM application experience. Multiple production systems built on top of frontier models (Anthropic, OpenAI, Gemini, open-weight). You know the practical edge cases: tool-use stability, structured-output failure modes, long-context degradation, prompt-injection defence, cost control.
- Agent systems depth. You've built something with real agent behaviour — planning, memory, tool orchestration, multi-step execution, error recovery — not a single prompt in a loop. Experience with multi-agent coordination (delegation, sub-agent protocols, MCP-style tool servers) is a strong plus.
- Multimodal experience. Hands-on work with vision-language models, document AI (OCR, layout, tables), or audio — end-to-end from ingest to grounded output.
- Strong engineering craft. Python at a senior level — async, typing, testing, packaging, observability. Able to read and navigate a large codebase. Git hygiene that makes reviewers' lives easier.
- Production AI engineering. You can take ML, LLM, embedding, vision, or multimodal models from prototype to production — designing APIs and inference services, building RAG/embedding pipelines, containerizing workloads, handling CPU/GPU deployment, and optimizing latency, throughput, reliability, and cost.
- AI platform & MLOps experience. Hands-on experience operating AI workloads in production with model/version management, CI/CD, evaluation gates, observability, autoscaling, rollback, and failure handling. Experience with Docker, Kubernetes/AKS, Azure AI services, GPU inference, or model-serving frameworks such as vLLM or NVIDIA Triton is a strong plus.
- Fluent with modern coding agents. You use Claude Code / Cursor / Copilot / equivalents daily as a force multiplier. You understand where they shine and where they fail, and you can design prompts, context and tool boundaries to get the most out of them.
- Communication. Writes and speaks clearly in English.
Additional Information
This position will be contracted through Bosch’s external vendor under a 1-year contract. Salary and benefits will be discussed during interview
