[Hiring] Full Stack Engineer @Zensar

Role Description

As a Lead, you’ll be hands-on in designing, building, and operating core distributed services. You’ll contribute to AI-powered features, influence component level architecture within the team, mentor junior engineers, and help accelerate delivery as we extend into new deposit-core integrations and scale toward hundreds of financial institutions.

In 2026, Revenue Connect is embedding AI throughout the product — from generative statement insights to anomaly detection and pricing optimization. You will implement and integrate these AI capabilities, advocate for safe and governed usage of models and data, and help upskill the team in AI-accelerated engineering practices.

What you will be doing:

• Translate complex or ambiguous requirements into clean, maintainable, scalable, and well documented code.
• Design, develop, and maintain software applications and systems that provide value to end-users.
• Implement AI-powered capabilities in collaboration with product and principal engineers.
• Implement and optimize algorithms, data usage, and cloud services for latency, availability, and cost.
• Debug and troubleshoot software issues to ensure business continuity, and a high bar for end-user experience.
• Raise the engineering bar via rigorous code and design reviews that enforce maintainability, security, performance, and AI safety.
• Write unit & integration tests, implement observability, and comply with best practices for builds and deployment to ensure the quality and reliability of our platform.
• Provide live on-call support by participating in the team on-call rotation and owning production issues from root cause analysis to resolution to future prevention.
• Partner with cross-functional teams (engineering, product, design, security, compliance etc.) to bring ideas to life.
• Mentor junior engineers; contribute to team knowledge sharing and AI upskilling.

Qualifications

• At a minimum, a Bachelor's in CS or equivalent experience.
• Typical qualifications for the role are 5 or more years of relevant professional experience or a combination of work experience and advanced education.
• Proven experience shipping AI-enabled features in production: model-driven decisions, anomaly detection, forecasting/optimization, or LLM-powered experiences—plus MLOps practices.
• Proficiency in at least one modern development framework / language (e.g., Java).
• Excellent communication and cross-functional collaboration skills to thrive in a fast-paced environment.
• Experience leading projects from architectural design to production, while setting and maintaining high standards of technical excellence across your team.
• Expertise in at least one area relevant to our cloud-based financial platform (e.g., fintech, distributed systems, databases, security, or front-end).
• Security, privacy, and compliance acumen for financial data (encryption, least-privilege, secrets management, auditability) and AI safety.
• Experience with version control systems (Git), and DevOps practices like continuous integration and continuous delivery (CI/CD).
• Leadership and communication. Track record leading projects from architecture to production, influencing cross-functional stakeholders, and mentoring engineers to raise the bar.

Requirements

• Proven ability to self-direct your technical work and scope projects effectively.
• Experience leading and mentoring junior engineers.
• Excellent communication and collaboration skills to influence both technical and non-technical stakeholders.
• Deep expertise in at least one area relevant to our cloud-based financial platform (e.g., fintech, distributed systems, databases, security, or front-end).
• Proficiency in modern development frameworks and languages (e.g., Java).
• Experience with version control systems (Git), and DevOps practices like continuous integration and continuous delivery (CI/CD).
• A strong understanding of security best practices for building enterprise applications.
• Prior work in fintech or billing/analysis systems, or large-scale anomaly detection/optimization problems.
• Hands-on experience integrating LLMs, RAG pipelines, model evaluation, or anomaly detection into production systems.

Benefits

• Flexible and creative work environment.
• Diverse and collaborative atmosphere.
• Professional and personal development resources.
• Opportunities to volunteer and support charities.
• Competitive salary and benefits.