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.