MUMBAI · FULLTIME

AI/ML Engineer

Kennect Solutions

Mumbai · onsite · Posted 6d ago

Sourced from Naukri

Undisclosed2–4 yrsfulltimeMumbai

Your match

Section · 01

About this role

Location: Mumbai

Role: Hybrid

Exp: 2-4 years

Role Overview

At Kennect, we are building a fully automated incentive management platform for some of India's largest enterprise companies, powering data-driven decision-making and sales incentive automation at scale. We are looking for proactive engineers with 2+ years of experience who want to build real AI and ML products, solve complex data problems, and take features from idea to production.

Key Responsibilities

Build automated systems, RAG pipelines, AI agents, and multi-agent workflows using LangChain and LangGraph.
Integrate AI agents into existing platform workflows and applications.
Work deeply with LLMs, tool calling, context management, evaluation, inference, latency, and cost optimization.
Design and optimize AI applications for production workloads, focusing on throughput, concurrency, reliability, and inference performance.
Build ML models for classification, pattern recognition, forecasting, anomaly detection, and predictive insights on sales and incentive data.
Work with enterprise datasets, embeddings, vector databases, retrieval pipelines, and data processing workflows.
Identify bottlenecks and architectural gaps, research solutions, and independently drive improvements.
Scale AI systems to support millions of users.
Handle large-scale data for machine learning applications and agent workflows.
Build deterministic and reliable agents.

Tech Stack

Python - Machine Learning and experimentation
Node.js / JavaScript - AI application backend and platform integration
LangChain / LangGraph - LLM applications and agentic workflows
Vector Databases - Embeddings, semantic search, and RAG
LLMs & Inference - Model APIs (AWS Bedrock), inference, optimization, and scaling

Preferred Background

2+ years of engineering experience with strong Machine Learning fundamentals and/or hands-on AI implementation experience.
Strong Python skills and hands-on experience building and deploying ML and AI models.
Understanding of classification, pattern recognition, forecasting, and model evaluation.
Ability to process and analyze large datasets.
Hands-on experience with LLMs, RAG, embeddings, and vector databases.
Strong understanding and experience with LangChain and LangGraph.
Strong understanding of LLM fundamentals, inference, evaluation, cost estimation, and production scaling.
Must have hands-on experience building and deploying applications using Node.js.

Qualifications

Strong problem-solving and system design fundamentals.
Must have hands-on experience building AI applications using Node.js and JavaScript.
Strong ownership and ability to independently identify and solve problems.
Comfortable working with ambiguity, messy data, and rapidly changing requirements.

What We Are Looking For

Strong fit if you've deployed in-house LLM models or worked on an inference server.
Engineers with 2+ YOE who have built real AI/ML or LLM applications.
ML engineers who have deployed ML models and have experience handling large-scale data.
AI engineers who have built more than just chatbots - including automated workflows.
Software engineers with strong fundamentals and hands-on GenAI experience.

Good to Have

Hands-on experience with llama.cpp and DuckDB.
Hands-on experience with MongoDB / PostgreSQL.
Knowledge of message queues like RabbitMQ.
Knowledge of different LLM architectures (e.g., MoE).

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Section · 02

Skills

AutomationPostgresqlmessage queuesmodel evaluationRabbitmqapisml engineerai modelsamazon web servicesvector databasesLarge Language Models (LLMs)PythonJavascriptMongoDBResearchSalesData ProcessingSystem DesignArtificial IntelligenceMachine LearningForecasting

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