AI Engineer

As a key member of cross-functional client-facing teams, develop and execute project plans to support initiatives that include, but are not limited to:
 

• Design, develop, and deploy AI/ML solutions and Generative AI applications to support commercial data and analytics for life sciences companies
• Integrate third-party AI APIs (e.g., OpenAI, Anthropic, Google Gemini, Hugging Face) into internal and client-facing applications to deliver intelligent, scalable solutions
• Build proof-of-concepts (POCs) and rapid prototypes to demonstrate the value of AI-driven approaches for product launch analytics, drug discovery, patient analytics, and data operations
• Develop and maintain internal tools and applications that streamline workflows, automate operational processes, and enhance team productivity using AI
• Build client-facing tools and services that leverage AI to deliver actionable insights, interactive dashboards, and intelligent recommendations
• Utilize cloud-service providers (e.g., AWS, Azure, or GCP) including services such as S3, EC2, Lambda, Azure OpenAI, and SageMaker to build and deploy scalable AI solutions
• Collaborate with onshore/offshore teams to ensure timely, high-quality deliverables, providing technical guidance and code reviews
• Design and implement data pipelines and ETL processes to support AI model training, fine-tuning, and inference workflows
• Investigate and evaluate emerging AI frameworks, tools, and models to continuously improve the team’s AI capabilities and stay ahead of industry developments
• Contribute to Blue Matter’s Internal platform rollout and other AI-powered product initiatives in client environments
• Address client questions, gather requirements, and deliver AI-powered solutions aligned with business goals
• Ensure project success through effective collaboration and meeting deadlines using agile delivery model
• Stay current with the latest advancements in AI/ML, LLMs, prompt engineering, RAG, agents, and related technologies, and evangelize best practices across the organization

Desired Experience and Skills
 

• Hands-on experience building AI/ML applications, including working with LLMs, Generative AI, and NLP frameworks
• Strong proficiency in Python and experience with AI/ML libraries and frameworks (e.g., LangChain, LlamaIndex, Hugging Face Transformers, PyTorch, TensorFlow)
• Proven experience integrating AI APIs (e.g., OpenAI, Anthropic, Google Vertex AI, Azure OpenAI) into production-grade applications
• Experience building and deploying internal tools and applications (e.g., using Streamlit, Gradio, Flask, FastAPI, or React)
• Ability to build client-facing tools and services that are reliable, user-friendly, and production-ready
• Expertise in building proof-of-concepts (POCs) and rapid prototypes to validate AI-driven solutions
• Experienced with cloud platforms (AWS, Azure, GCP) and services
• Proficient in API development (RESTful/GraphQL) and version control (e.g., Git)
• Expertise in SQL, Python, and databases
• Familiar with data pipeline tools (e.g., Airflow, dbt) and data warehouse technologies (e.g., Snowflake, Redshift, Databricks)
• Knowledge of prompt engineering, RAG (Retrieval-Augmented Generation), fine-tuning, and AI agent frameworks
• Strong knowledge of AI safety, responsible AI practices, and model evaluation techniques
• Knowledge of US pharma datasets and healthcare concepts is a plus
• Strong problem-solving, communication, and client-facing skills
• Proficient in Agile/Scrum and project management tools (e.g., JIRA, Smartsheet)
• Genuine passion and curiosity for ongoing AI development, with a demonstrated habit of learning and experimenting with new AI tools, models, and techniques
• Excellent communication and presentation skills (internal and client facing)

Preferred Qualifications:

• Advanced degree(s) BE/BTech in Computer Science, AI/ML, Data Science, or a related field
• 4+ years of AI/ML engineering experience (AI Engineer) or 6+ years (Senior AI Engineer), including client-facing roles experience
• Demonstrated ability to integrate business and industry knowledge in developing creative AI solutions
• Active contributions to open-source AI projects, personal AI projects, or published research in AI/ML
  • Passion for Generative AI and its applications in life sciences and healthcare