Lead Engineer

Who We Are

Arcadia is the AI-powered energy intelligence platform for businesses. We replace fragmented tools and manual workflows with one platform to pay utility bills, buy energy, and advance sustainability — across every location, at enterprise scale.

Trusted by Fortune 2000 companies, Arcadia combines unified data, AI-powered analytics, and expert advisory to help enterprise teams save money, mitigate risk, and cut carbon.

We deliver this through three comprehensive solutions:

• Utility Bill Management: Automating the entire utility bill lifecycle — from data capture and validation to payment processing and auditing.
• Energy Procurement Advisory: Bringing together comprehensive data, AI-powered analytics, market expertise, and a strong partner network to make sophisticated procurement options accessible to all.
• Sustainability Reporting — Verified emissions data with seamless integration into leading sustainability platforms.

Tackling the world's most complex energy challenges requires diverse thinking. We're building teams of people from different backgrounds, industries, and disciplines — united by a belief that energy management should be simple, intelligent, and a genuine driver of business value.

Benefits

• Competitive compensation based on market standards
• We are working on a hybrid model with remote first policy
• Apart from Fixed Base Salary potential candidates are eligible for following benefits
• • Flexible Leave Policy
  • Office located in the heart of the city in case you need to step in for any purpose
• We provide comprehensive coverage including accident policy and life insurance.
• Medical Insurance (1+5 Family Members)
• Flexible Benefit Plan
• Awards and Bonus
• Annual performance cycle
• Quarterly engagement activities
• A supportive engineering culture that values diversity, empathy, teamwork, trust, and efficiency

What We're Looking For

We are seeking a Lead Engineer to be the technical anchor of our Growth & Governance (GnG) squad in India — the team that acquires utility data from thousands of unreliable third-party sources, extracts and audits it, and turns it into the trusted dataset the rest of the Arcadia platform is built on. Formats change without notice, sources fail silently, and correctness is visible to customers, so our core expertise is building systems that stay accurate against data that refuses to cooperate.

This is a hands-on role with real ownership. You will own architecture for one or more of our services, lead projects end to end, act as a second point of technical review alongside the Engineering Manager, and mentor a team of earlier-career engineers.

AI has moved where the hard part of engineering sits. Producing code is no longer the bottleneck; deciding whether the produced code is the right answer is. We are looking for someone already well ahead on AI-driven development who also has the architectural judgment to reject its confident wrong answers — and to teach a team of earlier-career engineers to do the same rather than defer to the model.

What You'll Do

• Own the architecture and technical direction of one or more services in our acquisition, extraction, and audit pipeline, and lead medium-to-large projects on them end to end
• Translate ambiguous problems into engineering-ready designs, and decompose large efforts into pieces the team can build in parallel
• Act as a primary design and code reviewer — the second layer of judgment on AI-assisted designs and pull requests, catching architectural drift and silent correctness defects early
• Set the bar for AI-driven development on the squad — and bring your own view of what that should look like
• Own a category of reliability and technical-debt work end to end, without derailing roadmap commitments
• Share in the squad's production support rotation for the services you own, and improve what pages us
• Mentor earlier-career engineers: raise their design instincts, review quality, and independence
• Partner with Product, Operations, our Data Analytics Engineering team, and US-based engineering counterparts to shape requirements and drive cross-team initiatives

What Will Help You Succeed

Must-Haves

• Bachelor's degree in Computer Science or a related field, or equivalent practical experience
• 8+ years of software development experience at a SaaS or technology company, the majority building and operating backend or distributed systems in production
• A clear track record of owning projects end to end — from design through production — not just delivering assigned components
• Currently hands-on. You have shipped production code within the last two years
• Experience with enterprise Java (Spring / Spring Boot preferred) and Python
• SQL and relational data modelling at depth — you have designed schemas that survived real growth, and debugged correctness problems in the data rather than only in the code
• Experience building and operating high-volume data pipelines and third-party integrations, where correctness matters as much as throughput
• Experience with event-driven and asynchronous systems (streaming or queueing — Kinesis, Kafka, SQS or similar), including what goes wrong under retries and at-least-once delivery
• Deployed and operated systems on AWS or similar, on containerised platforms (Kubernetes / ECS)
• Production operability. You have owned services you were paged for — metrics and dashboards (Prometheus / Grafana, CloudWatch, Datadog or similar), structured logging, tracing, and alerts that fire on customer-visible symptoms rather than on every anomaly
• Strong AI-driven development practice. You work daily in agentic coding tools and are fluent at managing context and steering them across a large, unfamiliar codebase. AI is central to how this squad works, so you should already be ahead on it — with your own view of what good looks like and the judgment to know when the output isn't
• Architectural judgment. You can articulate the tradeoffs behind a design, choose the simpler option when it holds, and explain why you rejected the alternatives — including when the alternative came from a tool or from a more senior voice in the room
• Technical rigor. Testing strategy across the pyramid, observability and alerting built in rather than bolted on, security and maintainability treated as requirements
• Demonstrated mentorship. You've been the person a team goes to, and you've levelled others up
• Clear written and verbal communication. You write designs people can act on, and you work well with a distributed team across time zones
• Flexibility to join evening meetings up to ~8:30 PM IST to collaborate with US-based counterparts

Nice-to-Haves

• Experience shipping AI/LLM-backed features to production — latency, accuracy, cost, evaluation, and human-in-the-loop design
• Experience building SQL data pipelines (Snowflake + dbt preferred)
• Experience in the energy industry, or another domain requiring deep knowledge of messy, unreliable source data