AI Solution Engineer

Job title Associate AI Solution Engineer 1. JOB PURPOSETo design, develop, deploy, and support enterprise AI solutions using Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), intelligent chatbots, and AI agent frameworks. The role will focus on building secure, scalable, and business-ready AI applications for internal users and business functions including Research & Development, IT, Regulatory Affairs, Clinical Operations, Quality Assurance and corporate functions.The ideal candidate should have strong technical knowledge in Generative AI and should bring experience working in implementing intelligent systems that enable computers to understand, analyze, and reason with both visual and textual data in a manner similar to human cognition along with basic understanding of pharmaceuticaland biotechnology processes, regulatory documentation, SOPs, controlled documents, and compliance-driven environments. The Candidate should have basic knowledge of Software Development.2. DUTIES AND RESPONSIBILITIES AI Chatbot, RAG & Agent Development• Develop research and product roadmaps aligning with scientific and business objectives.• Develop AI-powered chatbots and virtual assistants for internal business users.• Build RAG-based applications that retrieve answers from SharePoint, PDFs, Word documents, SOPs, policies, databases, and internal knowledge repositories.• Create AI agent workflows for knowledge retrieval, document review, authoring, and business process automation.• Use frameworks such as Lang Chain, Lang Graph, Llama Index, Semantic Kernel, or similar tools under technical guidance.• Apply prompt engineering, grounding techniques, response validation, and evaluation methods to improve answer quality and reduce hallucinations.Data & Knowledge Integration• Support document ingestion pipelines for PDFs, Word files, Excel files, SOPs, regulatory content, and knowledge articles.• Work on chunking, metadata extraction, embeddings, vector indexing, semantic search, and citation- based response generation.• Use vector databases/search tools such as Azure AI Search, Azure Cosmos DBJob Description Template Revision Date: 1/2023 Job Description Template Revision Date: 1/2023Application Development & Deployment• Develop backend APIs and AI services using Python, FastAPI, Flask, or similar frameworks.• Develop document processing solutions using OCR, Natural Language Processing (NLP), and intelligent data extraction technique• Support deployment and maintenance of AI applications using Azure services, Docker, Git, and CI/CD pipelines.Security, Governance & Documentation• Follow organizational security, privacy, access control, and data governance standards while developing AI solutions.• Support responsible AI practices including auditability, monitoring, explainability, and controlled use of enterprise data.• Prepare technical documentation, user guides, architecture notes, test cases, and validation-support documents where required.3. QUALIFICATIONS• Bachelor's or master's degrees in engineering, Artificial Intelligence, Data Science, InformationTechnology, Machine Learning, or a related engineering discipline.• 2-5 years of experience in AI engineering, machine learning, data engineering, or applicationdevelopment.• Minimum 1 year of hands-on exposure to Generative AI, chatbot development, RAG solutions, LLM APIs, or AI agent-based applications.• Strong programming knowledge in Python, Java Scripts and basic understanding of APIs, databases, cloud platforms, and deployment practices.TECHNICAL SKILLSMust Have Python, REST APIs, SQL basics, GitHub, prompt engineering, LLM APIs, document processing AI / GenAI Generative AI, LLMs, RAG, embeddings, semantic search, response evaluation Frameworks Lang Chain, Lang Graph, Semantic Kernel, React, Node.jsCloud Microsoft Azure, Azure OpenAI, Azure AI Search, Azure App Services Vector DB/Search Azure AI Search Application Dev HTML/CSS, JavaScript basics, API integration DevOps Docker basics, CI/CD basics, deployment and monitoring awarenessBASIC PHARMA & BIOTECH KNOWLEDGE• The candidate should have basic awareness of pharma and biotech work environments so that AIsolutions can be aligned with business needs, document control expectations, and compliancerequirements.• Basic understanding of drug discovery, drug development, clinical trials, regulatory affairs, quality assurance, and manufacturing processes.• Awareness of SOPs, protocols, clinical study reports, investigator brochures, CTD modules, policies, and controlled documents.• Basic knowledge of GxP concepts, data integrity, audit trails, version control, document lifecyclemanagement, and approval of workflows.• Familiarity with regulatory references such as FDA, EMA, ICH guidelines, and 21 CFR Part 11 ispreferred.• Understanding AI uses cases in pharma/biotech such as regulatory document search, medicalwriting assistance, clinical knowledge assistant, pharmacovigilance triage, quality document review, and R&D knowledge management.PREFERRED CERTIFICATIONS• Microsoft Certified: Azure AI Engineer Associate or Azure AI Fundamentals.• Certification or practical training in Generative AI, LLM application development, machine learning, or cloud AI services.KEY COMPETENCIES• Strong analytical and problem-solving skills.• Ability to convert business requirements into AI-enabled solutions.• Good communication skills for working with technical and non-technical stakeholders.• Awareness of enterprise security, data privacy, and responsible AI principles.• Learning mindset with the ability to adapt to fast-changing AI technologies.SUCCESS MEASURES• Delivery of working AI chatbots, RAG applications, and AI agents for business use cases.• Improved knowledge retrieval and reduced manual search effort for users.• Accurate, grounded, and citation-supported AI responses.• Compliance with security, privacy, and data governance requirements.• Positive adoption and feedback from business stakeholders.