Senior Software Engineer - AI

Futops; Gurugram District; Hybrid; INR 2,400,000 - 4,200,000; Full time

Job summary

Futops is seeking a skilled Machine Learning Engineer to design, develop, and deploy ML models and AI-driven solutions. You will collaborate with clients, software engineers, and product teams to transform data into actionable insights and intelligent apps.

You will build agentic AI systems, deploy LLM-powered features, and own prompt engineering. The role requires strong Python, ML/NLP basics, and experience with SageMaker and Hugging Face in a fast-paced environment.

Qualifications

• 4+ years of Python (3.10+) production-grade code.
• Solid GenAI fundamentals including tokens, embeddings, and prompt engineering.
• Familiarity with A2A and MCP protocols.
• Basic ML/NLP knowledge: classification, regression, NLP pipelines, embeddings.
• Hands-on experience deploying models on AWS SageMaker.
• Familiarity with Hugging Face ecosystem.
• Experience with ML/AIOps CI/CD pipelines for model lifecycle.
• Strong data structures, algorithms and software engineering principles.
• Excellent problem-solving skills and ability to work independently.
• Good written and verbal communication skills.

Responsibilities

• Design and build agentic AI systems with tool use and multi-agent orchestration.
• Develop and deploy LLM-powered features: RAG pipelines and autonomous workflows.
• Own prompt and context engineering: manage context windows and token budgets.
• Build and maintain backend services using Python and FastAPI; design and manage SQL databases.
• Host and serve custom models on AWS SageMaker; manage endpoints and inference pipelines.
• Work with open-source models via Hugging Face; model selection and lightweight customization.
• Set up ML/AI-Ops workflows with CI/CD for model deployment and automated testing.
• Stay updated with ML, AI, deep learning, and agentic frameworks.

Skills

Python (3.10+)

GenAI fundamentals

Agent-to-Agent (A2A) & MCP

ML/NLP basics

AWS SageMaker

Hugging Face

ML/AIOps CI/CD

Data structures & algorithms

Problem solving

Communication

Tools

FastAPI

SQLAlchemy

Alembic

SageMaker

Hugging Face

Job description

Hiring for our esteemed client

What you will do (Immediate Joiners only)

We are seeking a highly skilled Machine Learning Engineer to design, develop and deploy machine learning models and AI-driven solutions. You will work closely with clients, software engineers and product teams to transform data into actionable insights and intelligent applications.

Responsibilities

• Design and build agentic AI systems - tool use, multi-agent orchestration, ReAct/chain-of-thought pipelines.
• Develop and deploy LLM-powered features: RAG pipelines, autonomous workflow automation.
• Own prompt engineering and context engineering: manage context windows, token budgets, and output structuring.
• Build and maintain backend services using Python and FastAPI; design and manage relational databases with SQLAlchemy and Alembic migrations.
• Host and serve custom models on AWS SageMaker; manage endpoints, scaling, and inference pipelines.
• Work with open-source models via Hugging Face - model selection, inference, and lightweight customisation.
• Set up and maintain ML/AI-Ops workflows - CI/CD pipelines for model deployment, automated testing, and continuous delivery of AI features.
• Stay updated with the latest advancements in ML, AI, deep learning, and agentic frameworks.

Must have

• 4+ years of experience in Python (3.10+) clean, production-grade code with async patterns and FastAPI.
• GenAI fundamentals: solid understanding of tokens, embeddings, prompt engineering, and context engineering.
• Familiarity with Agent-to-Agent (A2A) and Model Context Protocol (MCP).
• Basic ML/NLP knowledge: classification, regression, NLP pipelines, BERT, LIWC, Bag of Words, and embedding-based similarity models.
• Hands-on experience deploying and hosting custom models on AWS SageMaker.
• Familiarity with the Hugging Face ecosystem and open-source model landscape.
• Experience with ML/AIOps - CI/CD pipelines for model lifecycle, model versioning, monitoring, and automated evaluation in production.
• Strong grasp of data structures, algorithms, and software engineering principles.
• Excellent problem-solving skills with the ability to work independently and collaboratively in a fast-paced environment.
• Good written and verbal communication skills.