Senior Software Engineer

advantestcareers; Chennai District; On-site; INR 1,500,000 - 2,100,000; Full time

Job summary

advantestcareers is seeking a Senior Software Engineer to help build the backend and platform foundation for AI-assisted engineering automation. This role focuses on reliable backend services, long-running workflows, data and artifact handling, deployment, observability, and AI/ML integrations.

You will collaborate with AI and domain engineers to turn prototypes into scalable internal platforms used by engineering teams, with opportunities to grow into AI infrastructure, LLM integration, and

Qualifications

• 5-7 years of hands-on software engineering experience.
• Strong Python backend development.
• Experience with backend frameworks (FastAPI, Flask, Django).
• Experience with background jobs and workflow orchestration.
• Hands-on exposure to Redis, Celery, message brokers, caching.
• Docker and Linux deployment experience.
• Strong debugging, testing, data modeling, and code review skills.
• Ability to own ambiguous platform problems.

Responsibilities

• Build backend APIs and services for engineering automation workflows.
• Design and improve long-running job execution with worker queues.
• Handle engineering data, input files, configurations, logs, artifacts.
• Improve platform reliability via tests, logging, monitoring, error handling.
• Containerize, deploy, and operate services with Docker/Linux.
• Support concurrent users via scalable design and queues.
• Integrate platform services with AI assistants, local models, external AI services.
• Collaborate with algorithm/AI/domain engineers to translate workflows into software.

Skills

Python

FastAPI

Celery

Redis

Docker

Linux

Async processing

Data modeling

Code review

Ownership

AI assistants

Tools

Celery

Redis

Docker

Kubernetes

Job description

We are looking for a Senior Software Engineer to help build the backend and platform foundation for AI-assisted engineering automation. This role is ideal for someone who enjoys building reliable backend services, long-running workflow execution, data and artifact handling, deployment, observability, and integration with AI/ML services. The engineer in this role will help turn advanced prototypes into reliable internal platforms used by engineering teams. It is also a strong fit for platform engineers who want to grow into AI infrastructure, LLM integration, and agent-enabled engineering workflows.

WHAT YOU WILL DO

• Build backend APIs and services for engineering automation workflows.
• Design and improve long-running job execution using worker queues such as Celery/Redis or similar systems.
• Develop reliable handling of engineering data, input files, configurations, logs, intermediate outputs, final results, and versioned artifacts.
• Improve platform reliability through testing, structured logging, monitoring, error handling, and failure recovery.
• Containerize, deploy, and operate services using Docker and Linux-based environments.
• Support concurrent users and workloads through scalable service design, queue management, and resource-aware execution.
• Integrate platform services with automation engines, AI assistants, local models, and external AI/ML services.
• Work closely with algorithm, AI, and domain engineers to convert engineering workflows into maintainable software.

• 5-7 years of hands-on software engineering experience.
• Strong Python backend development.
• Experience with FastAPI, Flask, Django, or similar backend frameworks.
• Experience with background jobs, queues, workers, async processing, or workflow orchestration.
• Hands-on exposure to Redis, Celery, message brokers, caching, or equivalent systems.
• Docker and Linux deployment experience.
• Strong debugging, testing, data modeling, and code review skills.
• Ability to take ownership of ambiguous platform and product problems.
• Comfortable using AI coding assistants while critically reviewing generated code.

GOOD TO HAVE

• Experience building internal platforms, workflow tools, automation systems, or data-heavy applications.
• Object storage, artifact management, large-file handling, or result-versioning experience.
• Observability tools such as Prometheus, Grafana, OpenTelemetry, ELK, Loki, or similar.
• Kubernetes or container orchestration exposure.
• Interest or exposure to LLM engineering, AI agents, model-serving APIs, vector databases, GPU-backed workloads, or MLOps/LLMOps.
• TypeScript/frontend experience for engineering dashboards or visualization-heavy applications.
• Exposure to semiconductor test, validation, CAD/CAE, simulation, manufacturing, or engineering automation domains.