Job Title: AI Engineer-Products (Immediate Joiner)
About Improzo
At
Improzo (
Improve + Zoe; meaning Life in Greek), we believe in improving life by empowering our customers. Founded by seasoned Industry leaders, we are laser focused on delivering quality-led commercial analytical solutions to our clients. Our dedicated team of experts in commercial data, technology, and operations has been evolving and learning together since our inception. Here, you won't find yourself confined to a cubicle; instead, you'll be navigating open waters, collaborating with brilliant minds to shape the future. You will work with leading Life Sciences clients, seasoned leaders and carefully chosen peers like you!
People are at the heart of our success, so we have defined our CARE values framework with a lot of effort, and we use it as our guiding light in everything we do. We CARE!
- Customer-Centric: Client success is our success. Prioritize customer needs and outcomes in every action.
- Adaptive: Agile and Innovative, with a growth mindset. Pursue bold and disruptive avenues that push the boundaries of possibilities.
- Respect: Deep respect for our clients & colleagues. Foster a culture of collaboration and act with honesty, transparency, and ethical responsibility.
- Execution: Laser focused on quality-led execution; we deliver! Strive for the highest quality in our services, solutions, and customer experiences.
About The Role
We are seeking a
Product-oriented AI Engineer to build the intelligent engine behind our Pharma Commercial modules. In this role, you will build Python-based agents and RAG systems designed to optimize the Commercial Loopfrom personalizing HCP interactions to automating marketing content reviews. This is not just about prompt engineering; it is about building robust data pipelines that feed into
LLMs and
SLMs to drive real-world product outcomes. You will be responsible for translating complex customer pain points into reliable, scalable, and delightful AI Product experiences using a Big Data backbone that drive field-force effectiveness and brand performance.
Key Responsibilities
- High-Performance Python Engineering: Develop production-grade Python services using FastAPI or Pydantic to orchestrate AI Agents, ensuring asynchronous handling of long-running LLM tasks.
- Feature Ownership: Lead the technical design and implementation of AI features (e.g., automated reasoning, smart summaries, predictive agents) from ideation to production. Build Python-based agents that automate Next Best Action (NBA) logic, helping sales reps prioritize which HCPs to visit based on real-time prescription (Rx) data and sentiment analysis from CRM logs.
- Large-Scale RAG Orchestration: Architect Retrieval-Augmented Generation systems that interface directly with Big Data environments (Snowflake, Databricks, or Hadoop) to provide instant answers on product positioning, competitor intelligence, and formulary access.
- Big Data Intelligence: Leverage PySpark or Dask to preprocess, clean, and vectorize massive datasets for model grounding and fine-tuning.
- Commercial Data Intelligence: Leverage PySpark to process and vectorize massive commercial datasets, including Veeva CRM activity, IQVIA/Symphony claims data, and digital marketing engagement metrics.
- Agentic Logic & Tools: Build Python-based tools for agents that can query structured data warehouses, execute code, or interface with external APIs to fulfill user requests. Build AI Agents that don't just chat but perform multi-step actions using tools/APIs. You will optimize the chain of thought to ensure users get predictable, high-quality outcomes.
- Performance & Latency Engineering: Balance the use of LLMs (for complex reasoning) and SLMs (for speed and cost-efficiency) to ensure a snappy user experience.
- Data-Driven Iteration: Use product analytics and AI observability tools to identify where models fail in the real world and iterate on prompts, data chunks, or model architectures accordingly.
Role Requirements
- 5+ years of experience building software products, with at least 1.5 years focused on Generative AI.
- The Python Expert: You write clean, maintainable, and efficient Python code. You are comfortable with decorators, generators, and managing complex dependencies.
- Product Intuition: You understand that a model with 99% accuracy is useless if it takes 30 seconds to respond. You know when to trade off smartness for speed.
- Data Engineering Savvy: Ability to navigate complex Big Data environments to find and clean the data needed to ground your AI models. You are comfortable writing complex SQL or Spark jobs to extract the context your AI agent needs.
- Full-Stack Mindset: While you focus on AI, you are comfortable touching the API layer and collaborating closely with Frontend engineers on streaming responses and UI feedback loops.
- Privacy & Compliance: Familiarity with handling sensitive prescriber data and adhering to GDPR/CCPA and internal compliance walls between Commercial and Medical data.
Technical & Product Stack
Category
Requirements
Agentic/Generative AI
LangGraph, LangChain, LlamaIndex, OpenAI/Anthropic APIs.
Model Strategy
Experience with SLMs (e.g., Phi, Mistral) for low-latency tasks.
Big Data/Back-end
Python, FastAPI, Spark, Snowflake, or Databricks.
Vector Search
Expertise in semantic search (Pinecone, Milvus, or pgvector).
Product Evaluation
Ragas, Arize Phoenix, or LangSmith for vibe checks and hard metrics.
Model Ops
MLflow for tracking, Airflow for DAG orchestration of AI workflows.
Commercial Datasets
Experience with Rx data (IQVIA/Symphony), claims data, and HCP Master data
Benefits
- Competitive salary and benefits package.
- Opportunity to work on cutting-edge tech projects, transforming the life sciences industry
- Collaborative and supportive work environment.
- Opportunities for professional development and growth.
Skills: vector search,python,agentic/generative ai,rag orchestration,agents
