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Open nowPosted 5 hours ago

Senior AI Engineer

Workable (global search)106,891 open roles

Where
Bengaluru, KA, India
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Your applicationOpen nowSenior AI EngineerWorkable (global search) · Bengaluru, KA, India

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The clock on this job

Early applications get read.

9.5% of postings close within 7 days. Measured by our own scanner across the market. Workable (global search) postings stay open a median of 5 days.

Share of postings closed within
  1. 1.8%1 day
  2. 4.0%3 days
  3. 9.5%7 days
  4. 15.6%14 days
  5. 33.9%30 days
This job: posted 5 hours ago

Workable (global search) median: 5 days open

The posting

𝗧𝗵𝗶𝘀 𝗿𝗼𝗹𝗲 𝗶𝘀 𝗳𝗼𝗿 𝗼𝗻𝗲 𝗼𝗳 𝘁𝗵𝗲 𝗪𝗲𝗲𝗸𝗱𝗮𝘆'𝘀 𝗰𝗹𝗶𝗲𝗻𝘁𝘀

𝗦𝗮𝗹𝗮𝗿𝘆 𝗿𝗮𝗻𝗴𝗲: 𝗥𝘀 𝟰𝟬𝟬𝟬𝟬𝟬𝟬 - 𝗥𝘀 𝟱𝟱𝟬𝟬𝟬𝟬𝟬 (𝗶𝗲 𝗜𝗡𝗥 𝟰𝟬-𝟱𝟱 𝗟𝗣𝗔)

Experience: 5+ yrs

Location: Bengaluru, Karnataka, India

Job Type: Full-time

We are looking for an experienced Senior AI Engineer with strong expertise in Python, Rust, backend engineering, and production-grade AI systems to build and scale intelligent applications and AI-powered platforms. The ideal candidate will combine solid software engineering fundamentals with hands-on experience developing LLM-powered applications, AI agents, and scalable backend services.

You will play a key role in transforming AI capabilities into reliable production systems, focusing on performance, scalability, observability, and maintainability. This position is suited to an engineer who enjoys solving complex technical challenges, taking ownership of end-to-end delivery, and exploring modern AI technologies.

Requirements

Key Responsibilities

  • Design, build, and maintain production-grade AI applications and backend services using Python and Rust.
  • Develop and deploy LLM-powered applications, intelligent assistants, AI agents, and automated workflows.
  • Implement tool-calling, RAG pipelines, embeddings, vector search, and agent orchestration capabilities.
  • Build scalable APIs, asynchronous processing systems, database integrations, and reusable backend components.
  • Integrate external model APIs, inference services, and model-serving infrastructure into production applications.
  • Evaluate model and application performance, including response quality, latency, reliability, and resource utilisation.
  • Design robust service architectures with appropriate error handling, retries, security, and fault tolerance.
  • Deploy and manage services using Docker, Kubernetes, cloud infrastructure, and CI/CD pipelines.
  • Implement observability through structured logging, metrics, distributed tracing, dashboards, and alerts.
  • Troubleshoot production issues, conduct root-cause analysis, and drive continuous performance improvements.
  • Take ownership of engineering capabilities from technical design and implementation through deployment and ongoing operations.
  • Collaborate with product and engineering stakeholders to translate requirements into practical technical solutions.
  • Contribute to code reviews, architecture discussions, engineering standards, and technical documentation.
  • Explore emerging AI techniques and contribute to the evolution of a Rust-based AI platform.

What Makes You a Great Fit

  • 5+ years of professional software engineering experience, with strong proficiency in Python and/or Rust.
  • Hands-on experience building and deploying LLM-powered applications, AI agents, or production AI systems.
  • Strong understanding of RAG, embeddings, vector databases, semantic search, tool-calling, and agent workflows.
  • Solid backend engineering fundamentals, including API design, asynchronous processing, databases, and service architecture.
  • Production experience with Docker, Kubernetes, cloud platforms, and automated CI/CD workflows.
  • Familiarity with observability tools and practices involving logs, metrics, traces, and alerts.
  • Understanding of model APIs, inference pipelines, and model-serving infrastructure.
  • Strong debugging, problem-solving, and performance-optimisation skills.
  • Ability to independently own complex technical initiatives from concept through production.
  • Excellent written and verbal communication skills, with the ability to clearly explain technical gaps, risks, and trade-offs.
  • Interest in learning Rust and contributing to a Rust-based platform.
  • A strong ownership mindset and commitment to building reliable, scalable, secure, and maintainable AI systems.
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