AI/ML Engineer - Production AI & LLM Systems (India)

AI Engineer | India

Department: Engineering

Reports To: Product & Engineering Leadership

Location: India - Fully Remote

Employment Type: Full-Time

Experience Level: Mid-Level

Compensation: ₹15,00,000 – ₹22,00,000 per year (15–22 LPA), commensurate with experience and technical expertise

Position Overview

The AI Engineer at the company will design, develop, and deploy advanced, production-ready AI solutions, including Large Language Models (LLMs), Retrieval-Augmented Generation (RAG) systems, agentic AI workflows, and intelligent automation technologies.

This role requires a strong combination of AI research, hands-on model training and optimization, and software engineering expertise, with the ability to translate innovative AI concepts into scalable, reliable, and practical business applications.

Working closely with software engineers, product teams, and leadership, the AI Engineer will lead the development and integration of high-performance AI solutions that solve complex business challenges, enhance operational efficiency, and deliver measurable value to our global clients.

Key Responsibilities

AI System Development

• Design, develop, and deploy AI systems, including LLMs, RAG, agentic workflows, and ML/DL solutions.

• Select appropriate models and architectures while balancing accuracy, latency, cost, and complexity.

• Train and fine-tune models using PyTorch or Keras, including data preparation and evaluation.

• Implement and benchmark research methods before adoption.

• Build APIs, inference pipelines, and backend integrations.

Production & Optimization

• Own evaluation of metrics and track quality, latency, and cost.

• Monitor, debug, and optimize AI systems post-launch.

• Ensure production readiness and identify regressions before they impact users.

Collaboration

• Partner with software engineers and product teams to integrate AI into applications.

• Contribute to technical discussions and technical decision-making.

• Document architecture, implementation approaches, and key technical decisions.

Research & Experimentation

• Read and evaluate ML research papers.

• Implement promising methods and reproducing results where applicable.

• Adapt emerging techniques into production-ready systems.

• Contribute to continued innovation across AI and engineering initiatives.

Working Relationships

The AI Engineer will collaborate with

• Engineering leadership and product teams.

• Software engineers and backend developers.

• Global AI research and development teams.

Success in This Role

Success means you can build with AI and deliver reliable production solutions, not simply experiment with AI models.

You should be able to

• Deliver production-ready AI systems with measurable impact.

• Translate research into practical engineering solutions.

• Collaborate effectively across distributed teams.

• Document and share technical knowledge for scalability.

• Adapt to evolving technical and business priorities.

Work Environment

This is a fully remote position based in India. Candidates should be comfortable working independently and collaborating with globally distributed teams across different time zones.

Required Work Schedule

This AI Engineer role requires working Monday through Friday, 7:30 PM–4:30 AM or 8:30 PM–5:30 AM IST in India, depending on U.S. daylight saving time?

The ability to consistently work the assigned schedule is a required and non-negotiable condition of this role. Candidates must be comfortable working overnight hours and maintaining reliable availability throughout the assigned shift.

Due to project deadlines, production needs, client requirements, or other business priorities, occasional weekend availability or schedule adjustments may be required. Weekend work is not intended to be the standard schedule but flexibility to support business needs when necessary is expected

Our Hiring Process

We value your time and aim to keep our recruitment process transparent, efficient, and engaging.

• Initial Recruiter Screening

An introductory video call with a member of our Recruiting team to discuss your background, experience, career goals, salary expectations, and any initial questions you may have about the role or the company.

• Practical Skills Assessment

Candidates who successfully complete the initial screening will receive a practical assessment to complete asynchronously.

The assessment is designed to evaluate technical knowledge, problem-solving ability, and how you approach a real-world engineering scenario.

• Assessment Review

Our team will review your submission against the technical requirements of the role.

Candidates who meet the required criteria will advance to the final interview stage.

• Technical / Coding Interview

Candidates who pass the assessment will meet with our Engineering team to further evaluate their technical skills, experience, and AI Engineering knowledge

• Final Interview – CTO

A deep-dive conversation with our Chief Technology Officer focused on technical alignment, your assessment approach, architectural thinking, problem-solving, and overall alignment with the role and team.

Requirements

Required Qualifications

• 3+ years of hands-on AI/ML engineering experience, with at least one system deployed to production.

• Strong NLP fundamentals, including tokenization, embeddings, classification, NER, and information extraction.

• Strong engineering skills across coding, Git, testing, API/system design, and debugging.

• Hands-on model training experience using PyTorch or Keras.

• Understanding generative model architectures, including Transformers and VAEs.

• Production experience with LLMs, including RAG, embeddings/vector databases, and prompt/evaluation design.

• Experience with FastAPI or similar frameworks, Docker, and at least one cloud platform such as AWS, GCP, or Azure.

• Ability to read ML research papers and translate ideas into working code.

Preferred Qualifications

• Experience with LLM fine-tuning, including LoRA and RL-based methods.

• SQL database knowledge.

• Familiarity with agent frameworks such as LangGraph or LangChain.

• Experience with Kubernetes, CI/CD, and model-serving infrastructure.

• Open-source contributions or experience reproducing research results.

Benefits

Compensation & Benefits

• Annual Compensation: ₹15,00,000-₹22,00,000 (15-22 LPA), based on experience and technical expertise.

• Contract and payment administration facilitated through Deel.

• 90-day probationary period.

• Benefits eligibility upon successful completion of probation, including:

• Paid Time Off (PTO) in accordance with company policy.

• Holiday pay for company-observed holidays.

• Career growth and professional development opportunities.