Software Engineer (AI/ML + Python)

United States Digital Space LLC; Maharashtra; On-site; INR 1,200,000 - 1,800,000; Full time

Benefits offered by this job

Health insurance

Provident Fund

Job summary

United States Digital Space LLC is hiring a Python-focused Software Engineer (AI/ML) to design and deploy production AI systems for real-world business operations in Mumbai. You will work closely with customers, founders, and teams to build scalable backend services using FastAPI and Python, integrating LLM APIs and agentic workflows.

The role emphasizes production readiness, observability, and fast delivery from discovery to deployment.

Qualifications

• 2+ years of hands-on Python engineering experience.
• Experience building production AI systems and APIs.
• Familiarity with OpenAI, Anthropic, Bedrock or similar LLM APIs.
• Experience with backend services, testing, and deployment practices.

Responsibilities

• Collaborate with customers to translate requirements into production AI solutions.
• Design, build, and deploy AI-powered systems using modern ML tooling.
• Develop scalable backend services with Python and FastAPI.
• Implement observability, monitoring, and guardrails for production systems.
• Prototype quickly and ship features end-to-end with high velocity.

Skills

Strong Python

FastAPI

LLM APIs

Agentic workflows

RAG pipelines

Vector databases

Docker

Git

Debugging

Tools

Kubernetes

PostgreSQL

Job description

Role: Software Engineer (AI/ML + Python)/ Forward Deployed Engineer

Experience: 2+ YearsPayroll: the companyLocation: Goregaon, MumbaiReporting To: Team Lead

Please find the detailed Job Description attached below for your reference

Role Overview

We are hiring a Python / Forward Deployed Engineer to build and deploy production-grade AI systems for real-world business operations. This role sits at the intersection of backend engineering, AI implementation, customer delivery, and rapid product execution. You will work directly with customers, founders, and internal teams to design, build, deploy, and iterate AI-powered systems using modern LLM infrastructure, agentic workflows, and automation frameworks. This is not a research-only role. We are looking for engineers who can ship reliable systems fast, work in ambiguity, and own problems end-to-end.

Key Responsibilities

Customer-Facing Solution Engineering

Work directly with customers to understand workflows, operational bottlenecks, and automation opportunities. Translate ambiguous business requirements into production-ready AI systems. Own delivery from discovery and prototyping to deployment and iteration. Communicate technical trade-offs clearly across technical and non-technical stakeholders.

AI Systems & Agentic Workflows

Build AI-native applications using OpenAI, Anthropic, Bedrock, or similar LLM APIs. Design and implement agentic workflows, tool-using agents, multi-step reasoning pipelines, and autonomous task execution systems. Develop production-ready RAG systems with optimized retrieval and context orchestration. Implement structured outputs, memory handling, function/tool calling, and fallback strategies. Optimize prompts, latency, hallucination control, and inference cost. Build AI systems that are reliable, observable, and operationally stable — not demo-only prototypes.

Backend Engineering

Build scalable backend systems using Python and FastAPI. Design clean APIs and modular service architectures. Integrate external APIs, enterprise systems, databases, and automation platforms. Develop robust asynchronous and event-driven workflows where required.

Production Engineering

Containerize and deploy services using Docker and cloud infrastructure. Implement logging, monitoring, tracing, and operational guardrails. Debug failures across AI systems, infrastructure, integrations, and application layers. Maintain production reliability, scalability, and security standards.

Rapid Prototyping & Vibe Coding

Rapidly prototype and iterate using AI-assisted development workflows. Use tools like Cursor, Claude Code, Windsurf, Copilot, or similar AI coding environments effectively. Move quickly from idea to production without overengineering. Maintain engineering quality while shipping at high velocity.

Required Skills

• Strong Python engineering skills
• FastAPI / backend development
• REST APIs and system integrations
• LLM APIs (OpenAI, Anthropic, Bedrock, etc.)
• Agentic AI workflows and orchestration
• RAG pipelines and retrieval systems
• Vector databases (FAISS, Pinecone, Weaviate, MongoDB Atlas Vector Search, etc.)
• Prompt engineering and structured generation
• Docker and cloud deployment
• Git and software engineering fundamentals
• AI-assisted development / vibe coding workflows
• Strong debugging and systems thinking ability

Good to Have

• LangChain / LangGraph / LlamaIndex
• Async Python and distributed systems
• Kubernetes and CI/CD
• Observability tooling
• Workflow orchestration systems
• PostgreSQL / MongoDB / Redis
• Event-driven architectures
• Multi-agent systems
• Voice or multimodal AI systems

What We Expect

• Engineers who can operate independently in ambiguous environments.
• People who ship fast and iterate aggressively.
• Strong ownership mentality — not task executors waiting for instructions.
• Ability to communicate directly with customers and understand business context.
• Pragmatic problem solvers who prioritize outcomes over theoretical perfection.
• Engineers comfortable debugging messy real-world systems under pressure.

Preferred Candidate Profile

• Build quickly without producing fragile systems
• Can combine AI capabilities with strong software engineering fundamentals
• Are highly adaptable and learn new tools rapidly
• Think in workflows and systems rather than isolated code tasks
• Can move between customer conversations, architecture decisions, coding, and deployment seamlessly
• Use AI coding tools effectively instead of resisting modern workflows

Benefits

• Health insurance
• Provident Fund

Work Location: In person