AI Engineer

Bot Jobs; Bengaluru; Remote; INR 335,000 - 1,116,000; Full time

Job summary

Gunpowder Innovations is seeking an AI Engineer who can design and deploy advanced AI systems, including fine-tuning models and building agentic architectures. You will work remotely on global client projects, delivering production-ready AI capabilities and instrumentation.

The role emphasizes hands-on engineering across model selection, tooling, and deployment, with a focus on open-source stacks and scalable infrastructure. Strong experience with Python and ML infra is essential.

Qualifications

• Hands-on experience building agentic workflows and tool-calling logic.
• Proven ability to design and implement AI features from concept to production.
• Strong grasp of open-source LLM tools and deployment considerations.

Responsibilities

• Design and own architecture for AI-powered features across client projects.
• Build agentic systems with tool use and multi-step reasoning.
• Work with open-source models: fine-tuning, quantisation, evaluation, self-hosting.
• Create infrastructure around AI systems: retrieval, vector stores, monitoring, evals.
• Collaborate with clients to translate problems into working AI systems.

Skills

AI/ML

Generative AI

Agentic AI

Python

Tools

Docker

Kubernetes

VectorDBs

Job description

AI Engineer

• ₹30,000 – ₹1L No equity
• Remote (Everywhere)
• 3 years of exp
• Full Time

Job Details

• Hires remotely: Everywhere
• Remote Work Policy: Remote only
• Company Location: India
• Visa Sponsorship: Not Available
• Preferred Timezones: Maldives Time
• Relocation: Allowed
• Skills: Aiml, Generative AI, Agentic AI

About the job

About the role

We're building AI systems for clients who need more than a chatbot bolted onto an API. This role is for someone who can go deep: fine-tuning models, deploying open-source LLMs, building agentic systems, and designing the infrastructure that makes AI products actually work in production.

Key Responsibilities

• Design and own the architecture for AI-powered features across client projects, from model selection through to production deployment
• Build agentic systems: tool use, multi-step reasoning, orchestration frameworks, and the harnesses that let models act reliably in real environments
• Work hands-on with open-source models, including fine-tuning, quantisation, evaluation, and self-hosting where it makes sense
• Build the infrastructure around AI systems: retrieval pipelines, vector stores, inference optimisation, monitoring and evals
• Make the call on when to use a foundation model API versus when to fine-tune or self-host, and be able to justify it
• Collaborate directly with clients to translate ambiguous problems into working AI systems
• Stay ahead of the open-source and agentic tooling ecosystem so Gunpowder's clients get informed, current recommendations, not last year's stack

Requirements

• Real experience building agentic systems, fine tuning models and opensource work, not just prompting a hosted API
• Hands-on experience building agentic workflows: designing harnesses, tool-calling logic, and evaluation loops for agents that operate with real autonomy
• Strong grasp of the open-source LLM landscape: tools, frameworks, trade-offs, licensing
• Comfortable owning technical decisions end-to-end, from architecture to deployment
• Practical engineering skills: Python, ML infra (Docker, cloud deployment, vector DBs), and the judgement to know what's overkill and what isn't
• A builder's instinct: you'd rather ship something real than write another slide about AI strategy