About CustomerInsights.AI :

CustomerInsights.AI is a global analytics and AI-driven company founded in 2018, focused on enabling better commercial decision-making for Life Sciences organizations. Our product ecosystem, including ciPARTHENON and ciATHENA, leverages Analytics Automation, Artificial Intelligence, and Machine Learning to deliver faster, actionable insights to key stakeholders. With teams across North America and India, we partner with organizations ranging from startups to large enterprises.

Position Overview :

The AI Engineer will design, build, and deploy AI-enabled solutions that power customer and commercial insights, with a strong focus on automation, scalability, and production-grade AI engineering across analytics workflows.

Key Responsibilities :

- Design, develop, and deploy AI and machine learning solutions, including predictive models, NLP, and enterprise generative AI applications, to support customer and commercial analytics use cases.

- Build, customize, and operationalize copilot-style assistants, AI agents, and LLM-driven workflows to support analytics teams and business users.

- Build and optimize data pipelines, feature engineering workflows, and model inference services to enable reliable and scalable AI solutions.

- Drive automation of analytics and operational processes using AI, scripts, APIs, and workflow orchestration tools to improve efficiency and reduce turnaround time.

- Work in close collaboration with AI product managers and platform teams to translate product requirements into scalable, production-ready AI engineering implementations.

- Support model deployment, monitoring, and retraining workflows, ensuring performance, stability, and data quality in production environments.

- Document AI solutions, code, and processes to support maintainability, knowledge sharing, and regulatory readiness where applicable.

Required Qualifications :

- Bachelors or masters degree in computer science, Engineering, Data Science, Statistics, or a related quantitative discipline.

- 3- 5 years of hands-on experience building and deploying AI or machine learning solutions in real-world, production environments.

- Proficiency in Python and experience with machine learning frameworks such as TensorFlow, PyTorch, scikit-learn, or similar.

- Hands-on experience working in generative AI environments, including prompt engineering, copilot or agent-based frameworks, and orchestration of LLM workflows (e.g., OpenAI ecosystem, Azure OpenAI, or equivalent).

- Experience working with structured and unstructured data, including SQL-based data access and core data engineering concepts.

- Practical exposure to cloud platforms or modern data stacks (AWS, Azure, GCP, Databricks, or similar).

- Demonstrated ability to communicate complex AI concepts effectively to internal stakeholders and client audiences.

Preferred / Good to Have :

- Prior experience working with pharma, healthcare, or life sciences clients or datasets (commercial, RWE, clinical, or operational analytics).

- Exposure to MLOps practices, including model versioning, CI/CD for ML, monitoring, and experiment tracking.

- Experience integrating generative AI solutions into enterprise products or analytics platforms.

Personal Attributes :

- Strong technology enthusiasm with a continuous learning mindset around AI, GenAI, and emerging tools.

- Automation-first and operations-oriented thinking, with a focus on scalability, reliability, and efficiency.

- A structured problem solver who balances technical depth with business relevance.

- A collaborative team player, comfortable working across analytics, engineering, and AI product stakeholders.

Why Join Us?

- Play a key role in shaping the next generation of intelligent enterprise platforms

- Work at the intersection of cutting-edge AI and real-world business impact

- Collaborate with passionate engineers, data scientists, and domain experts

- Flexible work environment with a focus on continuous learning and innovation

Culture & Values :

We foster a high-ownership, performance-driven culture where teams are encouraged to think creatively, act responsibly, and deliver measurable outcomes. Our values guide how we collaborate, make decisions, and build long-term partnerships.