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3 mo agofound 5 d ago
Software Development Engineer - AI/ML
What the posting is about
Build and maintain AI-powered systems. Integrate LLM APIs into real-world workflows. Collaborate with cross-functional teams to turn product ideas into features.
Read out of the posting
LevelNot stated
Experience asked3+ years
EmploymentFull time
LocationIndia
RemoteYes
Visa sponsorshipNot stated
SalaryNot published, and most postings do not
Posted2026-07-03
Found viaworkable, direct from their system
We saw it 3 months after it went up.
The posting, as the company wrote it
Employment: Temporary
Experience: Entry level
Education: Unspecified
Company: Volga Partners
Location: Fully Remote (Occasional office visits 1–2 times per year)
Compensation: ₹19–₹24 LPA (based on experience)
Job Type: Full-time, Project-Based
Project Duration: Until the end of September 2026
Start Date: Urgently hiring — must be available to start within 1–2 weeks
Work Hours: 8:00 AM – 5:00 PM IST or 9:00 AM – 6:00 PM IST
(Collaboration with USA Pacific Time teams)
About the Role
Volga Partners is looking for a skilled Software Development Engineer with strong expertise in Python backend systems and AI/LLM applications.
In this role, you will build and maintain production-grade AI-powered systems, integrating large language models into real-world workflows. You will work across backend services, orchestration layers, and data pipelines—ensuring that AI features are reliable, scalable, and performant.
This is a hands-on engineering role requiring strong problem-solving, system design, and the ability to operate in fast-evolving AI environments.
Key Responsibilities
Build and maintain backend services and internal tools in Python for AI-powered applications.
Integrate LLM APIs into production workflows, including prompt handling, response processing, validation, and retries.
Design and implement scalable REST APIs, async workflows, and background job systems.
Maintain and enhance components of a multi-language codebase (C#/C++, Python, web technologies) where applicable.
Work with structured and unstructured data to prepare inputs, transform outputs, and support downstream systems.
Develop systems for prompt management, model routing, response validation, and failure handling.
Debug complex issues across backend logic, API integrations, and distributed services.
Monitor system performance using telemetry tools and proactively identify and resolve bottlenecks.
Automate recurring workflows related to data processing, evaluation, and reporting.
Collaborate with cross-functional teams to turn ambiguous product ideas into production-ready features.
Contribute to architecture decisions around scalability, performance, and safe use of AI systems.
Write clean, testable, and maintainable code while helping establish engineering best practices for AI systems.
What You Bring
Education
Bachelor’s degree in Computer Science or a related field.
Experience
3+ years of professional experience in backend or systems engineering.
Strong experience in Python development for production systems.
Experience integrating LLM APIs or AI-driven services into real applications.
Proven ability to work within large codebases and collaborative environments.
Technical Skillset
Core Skills
Python (strong), backend system design, API development
Async workflows, job queues, and service orchestration
Debugging across APIs, services, and data pipelines
Languages
Python, C#, C/C++, JavaScript/TypeScript, SQL
Frameworks & Libraries
.NET Web API, ASP.NET (MVC & WebForms), Entity Framework
React, Bootstrap, Ajax
Testing frameworks (xUnit or similar)
AI / LLM Systems
Prompt design, response parsing, and guardrails
Model integration patterns and failure handling
Understanding of LLM limitations and production constraints
Tools & Platforms
Azure DevOps, Git, Docker, Terraform
SQL Server or similar databases
Elastic Stack, Postman, Swagger
AWS or Azure cloud environments
Architecture
Microservices, distributed systems, modular architectures
Operating Systems
Windows, Linux
Build Tools
Make, Ninja (preferred)
Nice to Have
Experience with RAG, embeddings, vector databases, or retrieval systems
Familiarity with agent workflows or multi-step orchestration
Experience with model monitoring, prompt versioning, or evaluation systems
Understanding of AI safety, privacy, and secure data handling
Exposure to cloud-native deployments and scalable infrastructure
Why Join Us
Remote-first culture with minimal in-person requirements
Work with global teams on cutting-edge AI systems
Opportunity to build real-world LLM applications at scale
High ownership, fast-moving environment with strong growth potential
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