Job Description

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 28,200+ 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 Summary -

Bosch Research is seeking a highly accomplished and technically authoritative

Software Expert

in AI/ML Architecture to define, evolve, and lead the technical foundations of enterprise-grade, AI-driven systems. This is a

technical leadership role without people management responsibilities

, intended for professionals with deep expertise in

software architecture

,

AI/ML systems

, and large-scale

engineering applications

and their end-to-end deliveries.


You will own the architecture and technical delivery of complex software solutions--ensuring they are robust, scalable, and capable of serving diverse business domains and datasets. The ideal candidate demonstrates mastery in

cloud-native engineering

,

MLOps

,

Azure ML

, and the integration of AI Algorithms (Computer Vision, Text, Timeseries, ML, etc.),

LLMs

,

Agentic AI

, and other advanced AI capabilities into secure and high-performing software environments

Roles & Responsibilities:

Technical Architecture and Solution Ownership

Define, evolve, and drive

software architecture

for AI-centric platforms across industrial and enterprise use cases. Architect for

scalability, security, availability, and multi-domain adaptability

, accommodating diverse data modalities and system constraints. Embed

non-functional requirements (NFRs)

--latency, throughput, fault tolerance, observability, security, and maintainability--into all architectural designs. Incorporate

LLM

,

Agentic AI

, and foundation model design patterns where appropriate, ensuring performance and operational compliance in real-world deployments.

Enterprise Delivery and Vision

Lead the

translation of research and experimentation into production-grade solutions

with measurable impact on business KPIs (both top-line growth and bottom-line efficiency). Perform deep-dive

gap analysis

in existing software and data pipelines and develop long-term architectural solutions and migration strategies. Build architectures that thrive under

enterprise constraints

, such as regulatory compliance, resource limits, multi-tenancy, and lifecycle governance.

AI/ML Engineering and MLOps

Design and implement scalable

MLOps workflows

, integrating CI/CD pipelines, experiment tracking, automated validation, and model retraining loops. Operationalize AI pipelines using

Azure Machine Learning (Azure ML)

services and ensure seamless collaboration with data science and platform teams. Ensure architectures accommodate

responsible AI

, model explainability, and observability layers.

Software Quality and Engineering Discipline

Champion

software engineering best practices

with rigorous attention to:

Code quality

through static/dynamic analysis and automated quality metrics

Code reviews

, pair programming, and technical design documentation

Unit, integration, and system testing

, backed by frameworks like pytest, unit test, or Robot Framework Code quality tools such as SonarQube, CodeQL, or similar Drive the

culture of traceability, testability, and reliability

, embedding quality gates into the development lifecycle. Own the

technical validation lifecycle

, ensuring reproducibility and continuous monitoring post-deployment.

Cloud-Native AI Infrastructure

Architect AI services with

cloud-native principles

, including microservices, containers, and service mesh. Leverage

Azure ML

,

Kubernetes

,

Terraform

, and cloud-specific SDKs for full lifecycle management. Ensure compatibility with

hybrid-cloud/on-premise environments

and support constraints typical of engineering and industrial domains

Qualifications

Educational qualification:

Masteris or Ph.D. in Computer Science, AI/ML, Software-Engineering, or a related technical discipline

Experience:

15+ years in software development, including: Deep experience in

AI/ML-based software systems

Strong architectural leadership in

enterprise software design

Delivery experience in

engineering-heavy and data-rich environments

Mandatory/requires Skills:

Programming

: Python (required), Java, JS, Frontend/Backend Technologies, Databases C++ (bonus)

AI/ML

: TensorFlow, PyTorch, ONNX, scikit-learn, MLFlow(equivalents)

LLM/GenAI

: Knowledge of transformers, attention mechanisms, fine-tuning, prompt engineering

Agentic AI

: Familiarity with planning frameworks, autonomous agents, and orchestration layers

Cloud Platforms

: Azure (preferred), AWS or GCP; experience with

Azure ML Studio and SDKs

Data & Pipelines

: Airflow, Kafka, Spark, Delta Lake, Parquet, SQL/NoSQL

Architecture

: Microservices, event-driven design, API gateways, gRPC/REST, secure multi-tenancy

DevOps/MLOps

: GitOps, Jenkins, Azure DevOps, Terraform, containerization (Docker, Helm, K8s)

What You Bring

Proven ability to

bridge research and engineering

in the AI/ML space with strong architectural clarity. Ability to

translate ambiguous requirements into scalable design patterns

. Deep understanding of the

enterprise SDLC

oincluding review cycles, compliance, testing, and cross-functional alignment. A mindset focused on

continuous improvement, metrics-driven development

, and transparent technical decision-making.

Additional Information

Why Bosch Research?

At Bosch Research, you will be empowered to lead the architectural blueprint of AI/ML software products that make a tangible difference in industrial innovation. You will have the autonomy to architect with vision, scale with quality, and deliver with rigor--while collaborating with a global community of experts in AI, engineering, and embedded systems.