About the Company
Why We Built Lyric: Supply chains are more critical and complex than ever. Every day, large enterprises navigate trillions of possible decisions that could impact the bottom line. Powerful algorithms and AI can address these problems, yet most organizations struggle to leverage supply chain AI at scale. The current SCM technologies are either rigid, limited-scope point solutions or custom solutions built in-house, which demand immense expertise and investment.
That is…until now.
Enter Lyric: Lyric is an enterprise AI platform built specifically for supply chains, offering the best of both worlds:
Out-of-the-box AI solutions for optimizing networks, allocating inventory, scheduling routes, planning fulfillment capacity, promising orders, propagating demand, building predictions, analyzing scenarios, and more, plus
A platform-first approach that empowers both business and technical users with end-to-end product composability, leveraging no-code tools, their own code, or even forking our code to build and refine supply chain decision intelligence
With Lyric, enterprises no longer have to choose between flexibility and speed, they get both.
The Mission: We’re building a new era in supply chain with the team best equipped to lead it. With over 20 years at the intersection of supply chain and algorithms, we developed a deep conviction that global supply chains needed something like Lyric. Since our inception in December 2021, that conviction has been validated time and time again.
Today, a growing number of Fortune 500 companies, including Smurfit WestRock, Estée Lauder, Coca-Cola, Nike, and more, are innovating on their own terms with Lyric. We can’t wait to see what our customers, both current and future, are empowered to build with us next. Come build with us!
Software Engineer — Backend / PlatformWhat you’ll do
Build reliable services/APIs and data-heavy components that power forecasting, optimization, and simulations
Own design → implementation → rollout with tests, docs, and observability
Improve performance, reliability, and developer experience
What makes you a fit
Strong fundamentals in distributed systems, data modeling, and API design
Practical approach to testing, reviews, and incremental delivery
Comfort working cross-functionally with Product/DS/Infra
What you’ll do
Build intuitive, performant UIs for analytics, modeling, and scenario planning
Create reusable components and clean interfaces to backend services
Champion accessibility, UX clarity, and design system quality
What makes you a fit
Strong JS/TS and modern web app experience
Product sense: convert complex workflows into simple abstractions
Testing mindset and attention to detail
What you’ll do
Design data models, pipelines, and tooling that make ML/analytics trustworthy and fast
Establish data contracts, lineage, quality checks, and cost/scale guardrails
Enable self-serve data for product and science teams
What makes you a fit
Solid experience with batch/stream patterns and warehouse/lake paradigms
Focus on reliability, observability, and security
Builder of internal platforms or developer tools
What you’ll do
Define test strategy across services, data flows, and UI
Build automation, environments, and CI/CD quality gates
Drive release readiness and production monitoring signals
What makes you a fit
Hands-on in test automation and tooling
Comfortable reading code, isolating defects, and preventing regressions
Advocate for quality without slowing velocity
What you’ll do
Lead problem discovery and translate insights into crisp PRDs/RFCs
Prioritize outcomes, define metrics/NFRs, and ship iteratively
Align engineering, data, and design around simple, composable building blocks
What makes you a fit
Track record of shipping technical products 0→1 and 1→n
Clear writing, structured thinking, and data-informed decisions
Bonus: exposure to ML/LLM, optimization, or supply chain
What you’ll do
Build end-to-end ML services: data prep → training → eval → deploy → monitor
Productionize models with clear SLAs, rollback plans, and reproducibility
Blend classical methods with modern AI where they measurably help
What makes you a fit
Strong software skills plus practical ML experience
Familiar with experimentation and offline/online evaluation
Bias to automate, measure, and simplify
What you’ll do
Frame problems, analyze data, and ship models/insights that change decisions
Run experiments, define success metrics, and communicate trade-offs
Build explainable outputs users trust
What makes you a fit
Solid statistics/experimentation and hands-on analysis skills
Clear storytelling with data; impact-oriented mindset
Comfort collaborating with engineers and PMs
Real-world impact: your work moves inventory, capacity, and service levels at scale
Craft & community: small PRs, strong reviews, readable code, learning in public
Ownership & growth: autonomy with mentorship, competitive comp + ESOPs, remote-first (India) with a CHN/BLR/HYD/Pune heavy presence
