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Job description
Job Description: Tech Specialist - AI & Full-stack Systems
Role: Senior Individual Contributor (IC)
Reporting to: Management
Location: Pune, Maharashtra
Experience: 6–10 years
About Us: The Source JourneyAt Source, we are digitizing the backbone of India's economy by streamlining traditional supply chains through technology and lean operations.
2014 | The Spark: Mission to digitize India's fragmented industrial supply chains.
2017 | The Pivot to Lean: Focused on zero user behavior change and a profits-first mindset.
2020 | Digital Breakthrough: First Indian B2B firm with a WhatsApp API license; grew through COVID disruptions.
2022 | Scaling New Heights: Raised $1M from India SME Investments, scaling to ₹1,000 Cr+ topline profitably.
2025 | The 10x Era: Series A expansion into Recycled Polymers and Paints; moving 0.5M tons of material across India.
2026 & Beyond | The Mission Continues: Scaling to 1M tons, defining the future of Indian industrial distribution.
About the RoleWe are looking for a hands-on engineer to own complex technology initiatives from problem discovery to production-grade deployment and business outcomes.This is a senior individual contributor (IC) role focused on engineering depth, problem-solving, and architectural ownership—not team management. You will work directly with business stakeholders, design architectures, write production code, and build AI-native systems end-to-end. Key Responsibilities1. End-to-End Problem Ownership
Own complex technology initiatives across the full lifecycle: problem discovery, solution design, deployment, and post-launch outcomes.
Engage directly with business stakeholders to clarify ambiguous requirements, define actual problem statements, and align on scope.
Remain accountable for total business impact rather than just code delivery.
2. Architecture and Hands-on Engineering
Design and build scalable, reliable, secure, and maintainable software systems.
Drive technical choices, evaluate tradeoffs, and write production-grade code across backend services, APIs, and data pipelines.
Take projects from initial POCs to production deployment and long-term maintenance.
3. AI and LLM Engineering
Design, train, evaluate, and deploy Large Language Models (LLMs), including training models from scratch.
Build AI-native solutions that directly address core business workflows.
Handle the end-to-end model lifecycle: data prep, architecture, fine-tuning/RAG, inference optimization, latency/cost control, and production monitoring.
4. Delivery & Production Ownership
Deliver high-quality software on clear timelines by breaking complex tasks into milestones and proactively managing risks.
Own testing, CI/CD, deployment, monitoring, incident response, and continuous evaluation for traditional and AI software.
5. Technical Judgment & Improvement
Maintain high engineering standards and document key architectural decisions.
Continuously optimize systems to reduce complexity, lower operational costs, and improve system observability and developer productivity.
Eligibility Criteria
Education: Bachelor's degree in CS, Computer Engineering, IT, or related technical field. (Master's in CS/AI/ML preferred; equivalent strong industry experience accepted).
Experience: 6–10 years of hands-on software engineering experience delivering complex systems to production.
Required Technical Expertise
Backend Engineering: Proficiency in Node.js, TypeScript/JavaScript, API design, async processing, and event-driven architecture.
System Design: Expertise in distributed systems, scalability, database design, caching, messaging, and system integration.
AI/ML & LLM Engineering: Deep understanding of deep learning, transformer architectures, tokenization, attention mechanisms, GPU utilization, and LLM internals.
LLM Training: Direct experience training LLMs from scratch, fine-tuning, RAG, and serving models in production.
Frameworks & Languages: Python, PyTorch, or TensorFlow.
Data Engineering: Vector embeddings, data pipelines, dataset curation, and processing.
Infrastructure & Ops: Docker, CI/CD, cloud/on-prem deployment, monitoring, and logging.
Databases: SQL/NoSQL schema design, query optimization, and performance tuning.
Engineering Best Practices: Automated testing, code reviews, version control, and security best practices.
Profile & Mindset
Owner Mindset: Takes full responsibility for outcomes without needing every step defined.
Deep Problem Solver: Investigates business root causes and edge cases before designing software.
This page is for Indian job seekers preparing for JavaScript interviews, from freshers facing their first technical round to experienced developers targeting product companies. It covers 60 questions in three levels: easy questions on core language basics, medium questions on closures, this, promises and the event loop, and hard questions on polyfills, performance and tricky edge cases. Each answer is written the way a strong candidate would say it, with short code you can run in the browser console or Node. Read the answer, try the code, then explain it aloud in your own words.
Questions you may be asked
What is the difference between var, let and const?
What are the primitive data types in JavaScript?
What is the difference between == and ===?
What is the difference between null and undefined?
