Job Title: Lead AI Engineer

Experience: 7–9 Years (Minimum 3+ years in AI/ML and Generative AI, with 2+ years in Technical Leadership)

About Kalpita Technologies

Kalpita Technologies is a rapidly growing AI-first digital engineering company delivering innovative solutions across InsurTech, FinTech, Healthcare, Manufacturing, and Enterprise Technology. We specialize in AI Engineering, Cloud, Data, Application Development, DevOps, QA Automation, and Managed Services. As we expand our AI practice, we are looking for passionate technology leaders to architect and build next-generation AI-powered enterprise solutions.

Role Overview

We are seeking a highly experienced Lead AI Engineer / AI Solutions Architect to lead the design, development, and deployment of enterprise-grade Artificial Intelligence (AI), Generative AI (GenAI), Agentic AI, and intelligent enterprise application solutions.

This role combines deep technical expertise in AI engineering, cloud architecture, full-stack application development, and enterprise solution design. The ideal candidate will architect scalable AI platforms, integrate AI capabilities with modern application ecosystems, lead engineering teams, establish best practices, and collaborate closely with customers and business stakeholders to deliver high-impact AI solutions.

Key Responsibilities

AI Solution Architecture

Design and architect scalable AI, Generative AI, Agentic AI, and enterprise application solutions for customers.
Develop AI-powered applications using Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), AI Agents, and Multi-Agent systems.
Architect cloud-native, secure, highly scalable AI platforms, APIs, and enterprise applications.
Design integration strategies between AI solutions, backend services, frontend applications, and enterprise systems.
Define technical architecture, application frameworks, and technology roadmaps.

Technical Leadership

Lead technical design discussions, architecture reviews, and solution planning.
Mentor and guide AI engineers, data scientists, full-stack developers, and engineering teams.
Establish engineering standards, coding best practices, AI governance frameworks, and development guidelines.
Drive architecture decisions and technology roadmaps for AI and digital transformation initiatives.
Provide technical leadership across AI, cloud, backend, and frontend development teams.

AI Development & Enterprise Application Development

Develop intelligent applications using:

Large Language Models (OpenAI, Azure OpenAI, Claude, Gemini, Llama, Mistral)
Prompt Engineering
Retrieval-Augmented Generation (RAG)
AI Agents & Multi-Agent Frameworks
Knowledge Graphs
Semantic Search
Vector Databases
Model Fine-Tuning and Evaluation
Function Calling
MCP (Model Context Protocol)

Build enterprise-grade applications using:

.NET Core / ASP.NET Core
C#
Entity Framework Core
Microservices Architecture
REST APIs
FastAPI
Angular
TypeScript
HTML5
CSS3
Modern enterprise web application frameworks

Develop production-ready AI solutions using MLOps and LLMOps best practices.

Optimize AI model performance, latency, scalability, reliability, and operational cost.

Collaboration & Delivery

Work closely with product owners, business analysts, customers, and delivery teams to translate business challenges into AI-driven solutions.
Lead proof-of-concepts (PoCs), customer workshops, architecture discussions, and AI solution demonstrations.
Collaborate with application development teams to integrate AI capabilities into enterprise platforms.
Ensure successful deployment, monitoring, and continuous improvement of AI systems and applications.

AI Governance & Security

Establish AI governance, responsible AI practices, model monitoring, and compliance standards.
Ensure data privacy, security, explainability, and ethical AI implementation.
Implement AI observability, evaluation frameworks, and continuous model optimization.
Define security practices for AI applications, APIs, cloud platforms, and enterprise systems.

Required Technical Skills

Programming & Frameworks

Expert proficiency in Python.

Strong experience with:

PyTorch
TensorFlow
Hugging Face Transformers
Scikit-learn
FastAPI
REST APIs
.NET Core / ASP.NET Core
C#
Entity Framework Core
Microservices Architecture
Angular
TypeScript
HTML5
CSS3
Enterprise Full-Stack Application Development

Experience designing and developing scalable enterprise applications integrating AI/ML capabilities with modern backend and frontend technologies.

Generative AI

Hands-on experience with:

Large Language Models (LLMs)
Prompt Engineering
Retrieval-Augmented Generation (RAG)
Fine-Tuning & Model Evaluation
AI Agents & Multi-Agent Systems
Function Calling
MCP (Model Context Protocol)

AI Frameworks

Experience with one or more:

LangChain
LangGraph
LlamaIndex
CrewAI
AutoGen
Semantic Kernel

Vector Databases

Experience with:

Pinecone
Azure AI Search
ChromaDB
Weaviate
Milvus
FAISS

Cloud Platforms

Hands-on experience with:

Microsoft Azure
Azure OpenAI
Azure AI Foundry
Azure Machine Learning
AWS Bedrock
Amazon SageMaker
Google Vertex AI

DevOps & AI Operations

Experience with:

Docker
Kubernetes
Git
CI/CD Pipelines
MLflow
Azure DevOps
GitHub Actions
MLOps & LLMOps

Preferred Qualifications

Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Data Science, or a related field.
Azure AI Engineer, Azure AI Foundry, AWS Machine Learning, or Google Cloud AI certifications are highly desirable.
Experience in enterprise solution architecture and customer-facing consulting roles.
Strong experience designing AI-enabled enterprise applications.
Exposure to AI security, governance, Responsible AI, and AI compliance frameworks.

Soft Skills

Excellent leadership and mentoring abilities.
Strong analytical and problem-solving skills.
Outstanding communication and stakeholder management.
Ability to drive innovation and influence technical strategy.
Customer-focused mindset with strong presentation and consulting skills.

deveops engineer

Required Skills

Job Description

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