Improzo
Website:
improzo.com
Company:
https://www.linkedin.com/company/improzo
Industries: Pharmaceutical Manufacturing
Job details:
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 looking for an experienced and hands-on Lead Software Engineer to lead the design and development of core components of our next-generation Analytics Platform with a growing suite of AI-powered applications. In this role, you will combine strong technical depth with people leadership, guiding a team of engineers to build scalable, high-quality solutions in the data analytics and AI/ML space for the Life Sciences industry.
You will play a critical role in translating platform architecture into robust implementations, driving engineering best practices, and ensuring timely, high-impact delivery of features that empower our users across the Life Sciences value chain (Product Launch, Segmentation, Brand Management, Sales Force Effectiveness, Reporting & Dashboards, etc.).
Key Responsibilities
- Lead the design and development of key platform components for an AI-first Analytics and Applications platform.
- Act as a technical owner for major subsystems, ensuring alignment with overall platform architecture and product vision.
- Guide and mentor a team of software engineers specializing in Python (Django/Flask), data engineering, and AI/ML.
- Collaborate closely with Product Architects, Product Managers, and business stakeholders to translate architectural direction and requirements into high-quality technical designs and implementations.
- Drive the development and integration of advanced AI/ML and generative AI capabilities (LLMs, agents, workflows) into the platform for use cases such as Launch Planning, Field & HCP Engagement, Segmentation, and Personalization.
- Build and maintain scalable data pipelines and backend services using modern big-data technologies (Spark, Kafka, Databricks, Snowflake, etc.).
- Establish and enforce engineering best practices around coding standards, testing, security, performance, and observability.
- Own hands-on development, code reviews, and technical design reviews to ensure high-quality, maintainable solutions.
- Oversee CI/CD pipelines, DevOps practices, and cloud-native deployments using Docker, Kubernetes, and automated release workflows.
- Partner with data scientists and ML engineers to operationalize, deploy, and monitor AI/ML models in production.
- Foster a collaborative, Agile, and delivery-focused engineering culture that balances speed with quality.
- Contribute to hiring, onboarding, and performance development of engineering team members.
- Stay current with emerging technologies and trends in analytics, data engineering, and artificial intelligence, applying them pragmatically to product development.
Requirements
Qualifications & Skills
- Bachelor’s or Master’s degree in Computer Science, Engineering, or a related discipline.
- 6–10+ years of hands-on experience in building and scaling software products, with at least 2–3 years in a technical leadership or lead engineer role.
- Strong proficiency in Python and backend frameworks such as Django or Flask.
- Solid experience with data engineering and big-data ecosystems, including SQL/NoSQL databases, Spark, Kafka, Airbyte, Databricks, Snowflake, or similar technologies.
- Good understanding of data modeling, ETL/ELT pipelines, and data warehousing concepts.
- Experience working with at least one modern front-end framework (React, Angular, Vue.js, etc.) and collaborating closely with UI teams.
- Hands-on experience with cloud platforms (AWS preferred; Azure or GCP acceptable).
- Practical experience with CI/CD tools (Jenkins, GitLab CI, TeamCity), containerization (Docker, Kubernetes), and monitoring/logging solutions (Prometheus, Grafana, ELK stack).
- Exposure to integrating AI/ML models into applications; experience with generative AI, LLMs, and agent frameworks (e.g., CrewAI, LangChain) is a strong plus.
- Familiarity with security, compliance, and data privacy considerations (HIPAA, CCPA, SOC) in regulated environments.
- Knowledge of life sciences or biopharma domain and commercial datasets (IQVIA, Symphony, Komodo, Veeva, OCE, etc.) is highly desirable.
- Strong problem-solving skills with a pragmatic, delivery-oriented mindset.
- Excellent communication skills and the ability to influence across engineering, product, and business teams.
- High attention to detail, strong ownership mindset, and a bias for quality and customer impact.
Proven ability to mentor engineers and grow strong, high-performing teams.
Benefits
Benefits
- Competitive salary and comprehensive benefits package.
- Opportunity to lead and build cutting-edge analytics and AI-driven products for the Life Sciences industry.
- High-impact role with strong influence on technical direction and product outcomes.
- Collaborative, inclusive, and growth-oriented engineering culture.
- Opportunities for continuous learning, leadership development, and career progression.
Skills: software,design,hands-on technical leadership,python,postgresql,aws,framework,ci,data engineering,microservices architecture,life sciences
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