AI Engineer

Role Summary We are looking for an AI Engineer who can design, build, integrate, and maintain AI-driven features across multiple digital platforms. The role requires someone who can work across practical AI use cases including AI agents, conversational systems, automation workflows, image and document intelligence, recommendation logic, user-personalized journeys, analytics, and AI-assisted decision support. This is not a research-only role.

The person must be able to convert business problems into working AI solutions, integrate them into production systems, and collaborate with product, engineering, design, data, and business teams. Key Responsibilities- AI Product Development Build AI-enabled features for web and mobile platforms. Develop AI agents for task automation, user assistance, lead handling, decision support, and internal productivity.

Work on conversational AI flows across web, WhatsApp, email, and other channels. Design prompt flows, guardrails, workflows, and human-in-the-loop processes. Convert business requirements into AI workflows, APIs, and usable product features.

LLM and Agentic AI Work with LLMs such as OpenAI, Anthropic, Gemini, Llama, Mistral, or similar models. Build structured AI agents using tools, memory, retrieval, function calling, and multi-step reasoning. Design workflows for search, summarization, classification, recommendations, content generation, and decision support.

Implement RAG pipelines using company documents, structured datasets, APIs, and knowledge bases. Improve AI output quality through prompt engineering, evaluation, testing, and feedback loops. Data, Search and Intelligence Work with structured and unstructured data including documents, images, PDFs, databases, forms, and web content.

Build data extraction, classification, tagging, scoring, and matching workflows. Support AI-driven dashboards, insights, analytics, and automated reports. Create embeddings, vector search pipelines, and retrieval systems.

Work with data pipelines that can support personalization, matching, ranking, and recommendations. Integration and Engineering Integrate AI services with existing applications, APIs, databases, CRMs, CMS, and communication tools. Work closely with backend and frontend developers to deploy AI features into live products.

Build clean APIs and services for AI workflows. Support cloud deployment, monitoring, logging, and performance optimization. Ensure AI features are secure, scalable, cost-aware, and maintainable.

Testing, Governance and Quality Define test cases for AI outputs, edge cases, hallucination checks, and accuracy validation. Set up evaluation methods for prompts, models, and agent workflows. Document AI logic, assumptions, limitations, and improvement plans.

Follow privacy, security, and compliance expectations for sensitive data. Build AI workflows with proper audit trails, fallback logic, and human review where needed. Required Skills Technical Skills Strong experience with Python.

Experience with LLM APIs such as OpenAI, Anthropic, Gemini, Azure OpenAI, or similar. Understanding of prompt engineering, RAG, embeddings, vector databases, and AI agents. Experience with REST APIs and backend integration.

Familiarity with databases such as PostgreSQL, MySQL, MongoDB, or similar. Working knowledge of vector databases such as Pinecone, Weaviate, Chroma, FAISS, pgvector, or similar. Experience with cloud platforms such as Azure, AWS, or Google Cloud.

Basic understanding of frontend/backend product architecture. Ability to write clean, readable, production-oriented code. AI and Data Skills Text classification, summarization, entity extraction, document parsing, semantic search.

AI-assisted recommendations, scoring, matching, ranking, and personalization. Building structured workflows from unstructured data. Understanding of model evaluation, AI accuracy checks, and quality monitoring.

Familiarity with OCR, PDF parsing, image processing, or computer vision is preferred. Product and Business Skills Ability to understand business workflows and convert them into AI features. Strong problem-solving mindset.

Ability to work with product managers, designers, developers, and business teams. Comfortable working on multiple products and use cases in parallel. Ability to document clearly and communicate technical concepts in simple language.

Good to Have Experience with LangChain, LlamaIndex, CrewAI, AutoGen, Semantic Kernel, or similar agent frameworks. Experience with AI workflow automation tools. Experience with WhatsApp bots, chatbots, voice bots, or omnichannel AI assistants.

Experience with healthcare, travel, marketplaces, e-commerce, SaaS, or enterprise automation platforms. Experience with image datasets, classification models, or AI-assisted visual assessment. Experience with analytics tools, dashboards, and AI-led reporting.

Experience with secure handling of sensitive or regulated data. Expected Deliverables AI features integrated into live products. AI agents for internal and external use cases.

RAG pipelines and knowledge-based assistants. Document and data extraction workflows. Image classification or visual analysis workflows where required.

AI APIs and backend services. Prompt libraries, evaluation reports, and test cases. Clear technical documentation for AI workflows and integrations.

Candidate Profile The ideal candidate is hands-on, practical, and product-minded. They should not wait for perfect specifications. They should be able to understand the problem, suggest the right AI approach, build a working solution, test it, improve it, and support its deployment.

We are looking for someone who can move fast but still think clearly about quality, security, cost, and long-term maintainability. Education Bachelor’s or Master’s degree in Computer Science, Data Science, AI/ML, Engineering, or a related field. Equivalent practical experience will also be considered.

Reporting The AI Engineer will work closely with the Product, Technology, and Business teams and may coordinate with backend developers, frontend developers, data teams, QA, and domain experts depending on the project requirement.