About the internship:

DeepMechanix is focused on transforming research-grade AI systems into production-ready software that can operate reliably within regulated environments. The company builds robust backend infrastructure, scalable pipelines, and intelligent orchestration systems that power real-world AI applications. With a strong emphasis on performance, observability, and reliability, DeepMechanix ensures that advanced AI capabilities translate into deployable, efficient, and maintainable products.

Selected intern's day-to-day responsibilities include:

1. Develop and maintain FastAPI service layers for ingestion, inference, and calculation endpoints with proper async handling

2. Build and manage document ingestion pipelines from Azure Blob Storage through parsing, embedding, and vector storage

3. Design and implement LLM orchestration systems across multiple providers with rate limiting, fallbacks, and caching

4. Construct and manage storage architecture using PostgreSQL, vector databases, and programmatic SQLite integrations

5. Implement observability systems including structured logging, tracing, and performance dashboards

6. Conduct experiments with local LLM serving for optimized cost, latency, and throughput

7. Support backend infrastructure development to enable reliable and scalable AI deployment

8. Collaborate with teams to ensure system reliability, performance, and production readiness

Who can apply:

Only those candidates can apply who:

• are available for the work from home job/internship
• can start the work from home job/internship between 23rd Apr'26 and 28th May'26
• are available for duration of 3 months
• have relevant skills and interests
• are Computer Science Engineering students

Stipend:

INR₹ 75,000 - 1,25,000 /month

Deadline:

2026-05-23 23:59:59

Other perks:

Letter of recommendation, Flexible work hours

Skills required:

Python, PostgreSQL, HTTP, Docker, Microsoft Azure, English Proficiency (Spoken), CI/CD, FastAPI, Prompt Engineering, Object Oriented Programming (OOP), Amazon S3, Caching, System Design, LLMOps, LLM evaluation, Unit Testing and Integration Testing

Other Requirements:

• 1. Strong understanding of Python backend development, including OOP, async patterns, and FastAPI
• 2. Knowledge of prompt engineering, retrieval systems, embeddings, and RAG-based workflows
• 3. Familiarity with LLM-assisted development tools for coding, debugging, and architectural reasoning
• 4. Understanding of HTTP fundamentals including authentication, caching, and messaging systems
• 5. Experience with databases such as PostgreSQL and storage systems like Azure Blob Storage or AWS S3
• 6. Familiarity with development tools including Git, Docker, CLI, Linux, and CI/CD workflows
• 7. Knowledge of observability tools such as structured logging and tracing systems
• 8. Ability to use agentic coding tools effectively for faster implementation cycles
• 9. Enrollment in the third or final year of a Computer Science or related degree, or recent graduates with relevant experience
• 10. Experience in building and deploying backend systems with real users or production environments
• 11. Exposure to infrastructure, data engineering, or system design through projects or contributions
• 12. Strong problem-solving ability demonstrated through competitions, projects, or academic excellence
• 13. High academic performance or proven execution in real-world systems
• 14. Understanding of distributed systems concepts, data pipelines, or infrastructure as code is beneficial

About Company:

We build autonomous agents that design the hardware civilization runs on, static equipment, buildings, pipelines, bridges, power plants, CCS plants, fabs. Grounded in the engineering codes (ASME, AISC, API) and driving the 1990s-era desktop software that still runs every EPC/AEC on Earth. We collapse weeks of engineering into minutes. We're building toward Engineering General Intelligence (EGI), and a physical world that gets built faster, lighter, and lower in carbon.

Additional information:

• 1. Role focuses on building APIs, pipelines, storage systems, and observability infrastructure for AI products

2. Work involves integrating multiple LLM providers with cost and latency optimization

3. Daily work includes use of agentic coding tools and AI-assisted development environments

4. Working hours are primarily asynchronous with a daily 30-minute standup between 8–11 AM IST

5. Core stack includes Python, FastAPI, PostgreSQL, Azure Blob Storage, Docker, and CI tools

6. Application requires submission of a PDF CV along with GitHub profile and project links

7. Candidates must provide examples of deployed systems or detailed system design documentation

8. A short note on usage of agentic coding tools and their impact on problem-solving is required

9. Selection process includes a screening call, a technical interview, and a founder discussion