Engineering Lead, Finance (AI Tools )

Role: Engineering Lead, Finance (AI Tools)
Position Type: Full-Time Contract (40hrs/week)
Contract Duration: Long Term (with a possibility of contract to hire)
Work Schedule: 8 hours/day (Mon-Fri)
Location: Hybrid - 1x day onsite in Bangalore or Chennai

About the Role
We are seeking an Engineering Lead to set the technical direction for and lead the delivery of AI-powered applications and tools used across Product, Sales, Finance, Marketing, Customer Success, and Engineering. This is a hands-on leadership role: you will still design and build across the full stack while guiding architecture, raising engineering standards, and mentoring a team of engineers.
You will be accountable for how we build AI tools end to end from frontend and APIs through GenAI integration, deployment, and reliability and for ensuring the team ships high-quality, high-impact software.

What You Will Do
Technical Leadership

• Own the architecture and technical direction for a portfolio of AI tools and applications.
• Make and document key technical decisions (frameworks, patterns, build vs. buy) balancing speed, cost, and long-term maintainability.
• Establish engineering standards, review practices, and best practices for building with GenAI.
• Break down ambiguous business problems into a clear technical roadmap and deliverable milestones.

Team Leadership and Mentorship

• Lead, mentor, and grow a team of engineers through technical guidance, code review, enabling, and coaching.
• Plan and prioritize work across multiple workstreams, balancing delivery with quality and reliability.
• Foster a collaborative, high-ownership engineering culture.

Hands-On Full Stack and GenAI Development

• Remain hands-on: build frontends (Angular/React/TypeScript), backend services (Python/FastAPI or Node.js), and APIs for critical or complex components.
• Architect and build GenAI applications using OpenAI APIs, embeddings, vector search, RAG, LLM orchestration, and agentic workflows.
• Define evaluation frameworks and prompt engineering standards to ensure quality, safety, and cost efficiency.

Cloud, Data, and Integrations

• Own the cloud architecture on AWS (Lambda, S3, containers, API Gateway) and ensure scalable, secure deployments.
• Guide data and feature pipeline design using Python, SQL, and where relevant Databricks, Spark, and Delta Lake.
• Oversee integrations with enterprise systems (Salesforce, Oracle Fusion, Oracle Service Cloud, PeopleSoft) supporting real-time and batch workflows.

Reliability, Operations, and Support

• Establish monitoring and observability for application health, model drift, data quality, and prompt performance.
• Own L2/L3 support processes and lead root cause analysis, building preventive systems for long-term stability.
• Drive CI/CD, testing, and DevOps practices that keep delivery fast and safe.

Stakeholder and Cross-Functional Leadership

• Partner with Product, Engineering, Finance, Sales, Operations, Marketing, and customer-facing teams to align the technical roadmap with business priorities and clear ROI.
• Communicate technical strategy and trade-offs clearly to both technical and non-technical leadership.
• Champion adoption of AI tools through demos, documentation, and enablement.

Required Skills
Core Technical Skills

• Strong programming skills in Python and JavaScript/TypeScript, with deep full stack experience and proficient use of agentic coding tools like Claude or Codex to accelerate development/delivery.
• Proven experience architecting and shipping production applications (React on the frontend; FastAPI, Flask, or Node.js on the backend).
• Hands-on expertise with OpenAI APIs, LLM workflows, RAG, prompt engineering, and evaluation.
• Strong API and system design skills.
• Strong SQL and experience with large datasets and cloud data warehouses (Redshift, Snowflake, or similar).
• Solid experience deploying and operating on AWS.

Leadership Strengths

• Demonstrated experience leading or mentoring engineers and setting technical direction.
• Ability to design end-to-end solutions spanning UI, APIs, data, models, and automation.
• Strong communication, stakeholder management, and prioritization skills.
• Track record of delivering complex, cross-functional projects with measurable business impact.

Nice to Have

• Experience with vector databases and LLM frameworks (LangChain, LlamaIndex).
• Strong CI/CD, Docker, and infrastructure-as-code experience.
• Experience with MLflow or other MLOps/LLMOps platforms.
• Experience delivering customer-facing or enterprise GenAI applications at scale.
• Familiarity with Databricks, Spark, and Delta Lake.

Education

• Bachelor's degree in Computer Science, Engineering, or a related technical field is required.
• A master's degree or equivalent experience is a plus.