Lead AI Engineer
Required Skills
Job Description
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.