Senior AI Developer/AI Engineering Lead

Position: Senior AI Developer / AI Engineering Lead

Company Name: IBN Technologies Ltd
Location: Bibwewadi, Pune (Work From Office)
Working Hours: 10 am- 7 pm (Mon-Friday)
Type: Full-time Opportunity

Please find the JD below:

Senior AI Developer / AI Engineering Lead

Position Overview:

We are looking for a Senior AI Developer (3-5 years) with strong hands-on experience in AI/ML engineering, Generative AI, Agentic AI, AI-assisted development tools (Cursor.ai, GitHub Copilot, Claude Code, Windsurf, etc.), enterprise product architecture, and full-stack product development.

The role involves leading the design, architecture, development, and delivery of next-generation AI-powered CRM platforms, DIY automation systems, intelligent workflow engines, AI agents, copilots, APIs, and cloud-native SaaS products.

The candidate will lead a team of AI developers and product engineers while driving AI innovation, AI governance, scalability, cybersecurity, and product strategy.

This is a strategic technical leadership role for our next-generation AI + Cloud + Cybersecurity product ecosystem.

Key Responsibilities:

1. AI Strategy & Technical Leadership

• Lead AI product architecture and technology decisions across multiple product lines.
• Define AI development standards, coding frameworks, reusable AI components, and best practices.
• Mentor AI developers, full-stack engineers, and product teams.
• Drive AI adoption, innovation, and engineering excellence across the organization.
• Work closely with executive leadership, product management, cybersecurity, and cloud teams.

2. AI-Assisted Development & Generative AI

• Use Cursor.ai or similar AI coding tools to accelerate development.
• Build AI-powered features:
• Smart recommendations
• Data extraction & reconciliation
• CRM insights and automation
• Workflow bots and AI chat assistants
• Design and implement Enterprise AI solutions using Large Language Models (LLMs).
• Develop AI Agents, Multi-Agent Systems, AI Copilots, and Autonomous Workflows.
• Implement LLM-based modules using APIs like OpenAI, Anthropic, etc.
• Build Retrieval-Augmented Generation (RAG) pipelines and knowledge management systems.
• Implement Prompt Engineering, Agent Orchestration, Tool Calling, and Context Management frameworks.
• Evaluate and integrate emerging AI technologies and foundation models.

3. Full-Stack Engineering & Solution Architecture

• Develop front-end modules using React.js, Tailwind, modern UI frameworks.
• Build backend services using Node.js / Python.
• Implement REST or GraphQL APIs for multi-tenant SaaS products.
• Create reusable components for CRM, Finance, and Operations systems.
• Design scalable enterprise-grade architecture for AI-enabled SaaS products.
• Lead architecture reviews, performance optimization, and technical governance.
• Ensure high availability, scalability, resiliency, and maintainability of applications.

4. Database, AI Data Layer & Knowledge Systems

• Design and manage database schemas (PostgreSQL preferred).
• Write optimized queries, migrations, and integrations.
• Handle secure storage of structured and unstructured data.
• Design Vector Database architecture (Pinecone, Weaviate, Chroma, Milvus, pgVector, etc.).
• Implement semantic search, embeddings, document indexing, and enterprise knowledge repositories.
• Build AI-ready data pipelines and data governance frameworks.

5. Integrations & AI Ecosystem

• Integrate with third-party APIs (CRM, finance apps, cloud services).
• Build secure connectors and automation scripts.
• Integrate AI platforms, AI models, cloud AI services, enterprise applications, and automation frameworks.
• Build AI-powered integrations with ERP, CRM, HRMS, BFSI, cybersecurity, and cloud platforms.
• Develop API gateways, event-driven architectures, and AI orchestration layers.

6. Product Development & Innovation

• Work closely with senior engineers, product managers, and UI/UX teams.
• Convert workflows into functional modules.
• Maintain clean code quality and participate in code reviews.
• Own end-to-end delivery of AI products from concept to production.
• Drive innovation initiatives, proof-of-concepts (POCs), and AI experimentation programs.
• Collaborate with business stakeholders to identify AI opportunities and product enhancements.

7. Security, Governance & Compliance

• Follow secure coding guidelines aligned with DPDP, SOC, and cloud practices.
• Ensure tenant isolation, input validation, and secure API design.
• Work with cybersecurity teams on VAPT fixes.
• Implement AI Governance, Responsible AI, Model Risk Management, and AI Security controls.
• Ensure compliance with DPDP, GDPR, SOC 2, ISO 27001, RBI, SEBI, and BFSI security requirements where applicable.
• Establish LLM security controls against prompt injection, model poisoning, data leakage, and AI threats.
• Lead secure AI architecture reviews and cybersecurity assessments.

8. Cloud AI, MLOps & LLMOps

• Design and deploy AI workloads on Azure, AWS, and Google Cloud.
• Implement MLOps and LLMOps pipelines for model lifecycle management.
• Build automated CI/CD pipelines for AI models and SaaS applications.
• Manage AI observability, monitoring, performance metrics, and governance.
• Optimize AI infrastructure costs and resource utilization.

Required Skills (Must Have)

• Experience using Cursor.ai or AI-assisted coding environments.
• Strong JS/TS skills and experience with React.js.
• Hands-on backend development with Node.js and/or Python.
• Solid database experience:
• PostgreSQL (preferred)
• Schema design, indexing, performance tuning
• Experience building APIs (REST/GraphQL).
• Strong understanding of cloud platforms Azure/AWS/GCP.

AI Expertise

• Hands-on experience with Generative AI, LLMs, Agentic AI, and RAG architectures.
• Experience with OpenAI, Azure OpenAI, Anthropic Claude, Gemini, Mistral, Llama, or equivalent models.
• Experience with LangChain, LangGraph, CrewAI, AutoGen, Semantic Kernel, or equivalent frameworks.
• Knowledge of vector databases, embeddings, and semantic search.
• Understanding of AI security and responsible AI practices.

Leadership

• Experience leading engineering teams,, and AI initiatives.
• Strong stakeholder management and decision-making capabilities.
• Ability to drive product architecture and technology roadmaps.

Good-to-Have Skills (Bonus)

• Experience with:
• LLMs, embeddings, vector databases
• LangChain / RAG pipelines
• Multi-tenant SaaS architecture
• CRM or finance system development
• Basic DevOps (GitHub Actions, CI/CD, Docker).
• Kubernetes, Terraform, Infrastructure as Code (IaC).
• AI Agent frameworks and workflow orchestration platforms.
• BFSI, FinTech, ERP, GRC, Cybersecurity, and Compliance domain experience.
• Experience building AI-powered SaaS products from concept to scale.

Soft Skills

• Fast learner, comfortable with AI-driven workflows.
• Strong problem-solving and debugging skills.
• Good communication and ability to work in cross-functional teams.
• Ownership mindset with attention to detail.
• Strong leadership and mentoring capabilities.
• Strategic thinking with business and product orientation.
• Ability to manage multiple stakeholders and priorities.
• Strong presentation and executive communication skills.

Qualifications

• Bachelors degree in computer science, IT, Engineering, or equivalent experience.
• Masters degree in computer science, Artificial Intelligence, Data Science, or related field (preferred).
• Relevant AI/Cloud certifications preferred.
• 3–5 years of hands-on software engineering experience.
• Minimum 2–3 years of experience leading AI, ML, or Generative AI initiatives.
• Experience delivering enterprise-scale SaaS and AI products.