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

- Solid 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).

📌 AI/ML Engineer (Mumbai)
🏢 Kennect Solutions
📍 Mumbai