Artificial Intelligence Consultant

Technical Lead AI Consultant)

India, Remote Role

• Design end-to-end AI, ML, and GenAI solution approaches aligned with business objectives.

• Translate complex pharmaceutical and business problems into AI-enabled solution designs.

• Define solution components such as data inputs, AI models, GenAI workflows, APIs, user interfaces, orchestration layers, and deployment patterns.

• Evaluate and recommend suitable AI models, LLMs, frameworks, cloud services, vector databases, and automation tools.

• Create solution design documents, technical blueprints, architecture diagrams, and implementation roadmaps. 2. GenAI & Applied AI Solutioning

• Design GenAI solutions using LLMs, RAG pipelines, prompt engineering, agents, knowledge search, summarization, automation, and workflow augmentation. Driving Innovation, Empowering Insights

• Identify opportunities where AI can improve productivity, decision-making, analytics, and business processes.

• Define build-vs-buy considerations for AI solutions and recommend appropriate technology stacks.

• Develop proof-of-concepts or prototypes to validate solution feasibility.

• Guide teams on responsible AI, explainability, model limitations, and risk mitigation.

3. Problem Framing & Business Translation

• Work closely with business stakeholders to understand needs, pain points, workflows, and success criteria.

• Convert business requirements into AI use cases, functional specifications, and technical solution designs.

• Assess data availability, feasibility, complexity, risks, dependencies, and expected business impact.

• Prioritize AI use cases based on value, feasibility, scalability, and adoption potential.

• Communicate solution options, trade-offs, risks, and recommendations to both technical and non-technical audiences.

4. End-to-End Delivery Ownership •

Own the solution lifecycle from ideation to design, prototype, implementation support, deployment, and adoption.

• Partner with AI/ML engineers, data engineers, cloud architects, application teams, and platform teams to deliver production-ready solutions.

• Ensure solutions are scalable, secure, maintainable, and aligned with enterprise architecture standards.

• Support productionization through MLOps, LLMOps, monitoring, governance, and continuous improvement practices.

• Track business outcomes and ensure solutions deliver measurable impact.

5. Collaboration with Engineering & Platform Teams

• Provide technical direction to development and engineering teams during implementation.

• Collaborate on API design, data pipeline integration, model deployment, prompt management, vector search, and cloud architecture.

• Ensure AI solutions are designed for reliability, performance, security, privacy, and compliance.

• Review implementation approaches and help resolve design or integration challenges.

• Act as a bridge between business teams, AI teams, and technology delivery teams. Driving Innovation, Empowering Insights 6. Pharmaceutical Domain Application

• Apply AI and GenAI solutions across pharmaceutical domains such as: o Clinical trials o Real-world evidence o Medical affairs o Drug discovery o Commercial analytics o Patient analytics o Regulatory and safety operations o Sales and marketing effectiveness

• Understand pharma data types, workflows, compliance expectations, and business challenges.

• Ensure AI solutions consider regulatory, data privacy, security, and ethical AI requirements.

• Support use-case design for regulated and sensitive healthcare environments. Technical Expertise Required Skills • Strong understanding of AI, machine learning, GenAI, and applied analytics concepts.

• Ability to design AI solutions without being limited to hands-on model development.

• Experience with Python and SQL.

• Good understanding of ML models, statistical methods, deep learning, NLP, and LLM-based systems.

• Experience designing or working with: o LLMs and GenAI platforms o RAG architectures o Vector databases o Prompt engineering frameworks o AI agents and workflow automation o APIs and application integration patterns o Cloud platforms such as AWS or Azure o MLOps or LLMOps practices Driving Innovation, Empowering Insights Architecture & Solution Design Skills

• Proven ability to design end-to-end AI/ML/GenAI systems.

• Understanding of data pipelines, model serving, cloud deployment, orchestration, monitoring, and governance.

• Ability to create solution architecture diagrams, technical design documents, and implementation plans.

• Experience evaluating tools, models, platforms, and frameworks based on business and technical needs.

• Understanding of scalability, security, privacy, performance, and maintainability considerations. Pharmaceutical Domain Knowledge • Experience delivering AI, analytics, automation, or GenAI solutions in the pharmaceutical, healthcare, life sciences, or related industries.

• Familiarity with pharma datasets, business processes, and industry challenges. • Understanding of compliance and privacy considerations such as GxP, HIPAA, GDPR, or similar frameworks is preferred.

• Ability to engage with domain stakeholders and convert domain problems into practical AI solution designs.

Experience Requirements • 6–8 years of experience in AI, data science, analytics, solution design, or technology consulting roles. • Demonstrated experience designing and delivering AI/ML or GenAI solutions. • Experience working with business stakeholders to define use cases and solution approaches. • Experience collaborating with engineering teams to implement and productionize AI solutions. • Prior experience in pharma, healthcare, or life sciences is strongly preferred. Soft Skills • Strong solution-oriented thinking and structured problem-solving ability. • Excellent communication and stakeholder management skills.