Engineering Lead
Location: San Francisco
Company Stage: Seed / Series A (just raised $10M+)
Team: Engineering
Experience: 6–10+ years
Compensation: Competitive + Metrics-Based Bonus + Equity
Why Join Cred?
CRED is an AI Native Command Center for businesses. It centralizes internal and external data for companies and matches it with external insights to help companies make better decisions and predict the future. With early traction in sports and entertainment and working with some of the biggest names like the PGA, Warriors and others and a fresh $10M+ venture round, we're scaling quickly. CRED’s dataset is one of the largest business databases in the world, and includes data on customers, people and companies and many related business entities. CRED collects and trains LLM Agents using internal and behavioral data to improve customer outcomes.
At CRED, you’ll have ownership, influence, and the opportunity to work at the intersection of AI, data, and business strategy. We move fast, execute in weekly sprints, and build with purpose. If you’re excited by high-impact work, tight feedback loops, and a role that touches product, customer, and data — this is for you.
What You’ll Be Working On
As Engineering Lead at Cred, you’ll shape how we build. You’ll manage and mentor a growing team, drive best practices across delivery and QA, and help us scale our infrastructure, pipelines, and platform with AI and automation at the core.
Key Responsibilities:
Lead and scale the engineering function with a strong delivery mindset — shipping high-quality features weekly
Own and evolve internal processes around CI/CD, QA automation, observability, and DevOps
Design and build internal tools to automate development, QA, and data workflows , powered by AI
Work closely with Product to scope and plan features, break down technical work, and ensure quality and stability
Mentor, manage, and motivate engineers through structured sprint planning, accountability, and growth conversations
Set standards for code quality, documentation, testing, and deployments
Guide architectural decisions across products including our AI agent, Chrome extension, data platform, and integrations
Maintain a strong pulse on delivery, helping to unblock technical issues and prioritise ruthlessly
Drive innovation around multi-platform builds , from web to Chrome and native apps
What We’re Looking For
Must-Haves:
6–10+ years of hands-on engineering experience, with at least 2+ years in engineering leadership roles
Proven ability to lead agile/scrum teams , set goals, track velocity, and manage delivery in sprint cycles
Strong background in DevOps and QA best practices — CI/CD pipelines, automated testing, infrastructure as code
Experience building and scaling data-rich products — including APIs, integrations, scraping tools, or cloud platforms
AI-native mindset — you actively look for ways to integrate LLMs and automation into engineering processes
Experience managing cross-functional teams , working closely with product and design
Passion for hands-on work — you enjoy building, debugging, and exploring technical edge cases
Excellent communication and storytelling — you can translate complexity for any audience and align teams around a plan
High ownership and bias for execution — you take pride in results and always find a way to move things forward
Bonus Points For:
Background in data integration, CRM, sales/marketing tooling or AI-first products
Experience with data science models and building AI/ML infrastructure & AI-first products
Strong cloud infrastructure skills (AWS, GCP, or Azure)
Built internal tools or systems for QA automation, observability, or CI/CD workflows
Familiarity with building Chrome extensions, Mac apps , or multi-platform tooling
Sound like you?
If you're a structured, hands-on engineering leader who thrives on accountability, shipping fast, and building AI-native infrastructure — let’s talk.
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