Description review
Full Stack Software Engineer
Clera · United States · back to the listing
HR standards
67/100
needs work
Title ↔ description
90/100
strong
Reads as
Full-Stack Engineer
100% confident
How others title the same work
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About the Role
This is a full stack engineering role at an early-stage AI-native consumer intelligence platform, where you'll own features end-to-end — from backend services processing enterprise data at scale to the frontend interfaces that make that intelligence actionable. In a small, fast-moving team, you'll work closely with enterprise customers and ML engineers to ship product that directly shapes how leading brands understand their consumers.
What You'll Do
• Build and ship features across the full stack — backend services in Go/Python and frontend experiences in React/TypeScript.
• Design APIs, data models, and service architectures that support agentic AI capabilities.
• Create intuitive interfaces that translate complex enterprise data into clear, actionable workflows.
• Collaborate with ML engineers to bring AI-driven features from prototype to production.
• Own features through the full lifecycle: scoping, architecture, implementation, testing, deployment, and iteration.
• Work directly with enterprise customers to understand real-world needs and refine the product.
• Contribute to infrastructure, tooling, and developer experience as the engineering team scales.
What We're Looking For
• 3+ years of professional engineering experience, with at least 2 years in early-stage startup environments shipping end-to-end product.
• Proficiency in both TypeScript/React and at least one of Go or Python, with a track record of shipping code in both frontend and backend layers.
• Experience with AWS or equivalent cloud infrastructure and modern deployment practices.
• Experience building or deploying data pipelines or data engineering work.
• Strong product instincts — you think about the user, not just the code.
• Comfortable owning loosely-scoped problems and moving from ambiguity to shipped feature independently.
• Bachelor's degree in Computer Science or a related field.
• Bonus: experience with LLM integrations, agentic AI systems, or RAG architectures; background in enterprise SaaS, retail technology, or data-intensive products; familiarity with data visualization or streaming architectures.
Compensation & Benefits
Base salary range: $120,000 – $200,000 USD annually. Visa sponsorship is not available.
Location
On-site in New York, NY.
Originally posted on Himalayas
This is a full stack engineering role at an early-stage AI-native consumer intelligence platform, where you'll own features end-to-end — from backend services processing enterprise data at scale to the frontend interfaces that make that intelligence actionable. In a small, fast-moving team, you'll work closely with enterprise customers and ML engineers to ship product that directly shapes how leading brands understand their consumers.
What You'll Do
• Build and ship features across the full stack — backend services in Go/Python and frontend experiences in React/TypeScript.
• Design APIs, data models, and service architectures that support agentic AI capabilities.
• Create intuitive interfaces that translate complex enterprise data into clear, actionable workflows.
• Collaborate with ML engineers to bring AI-driven features from prototype to production.
• Own features through the full lifecycle: scoping, architecture, implementation, testing, deployment, and iteration.
• Work directly with enterprise customers to understand real-world needs and refine the product.
• Contribute to infrastructure, tooling, and developer experience as the engineering team scales.
What We're Looking For
• 3+ years of professional engineering experience, with at least 2 years in early-stage startup environments shipping end-to-end product.
• Proficiency in both TypeScript/React and at least one of Go or Python, with a track record of shipping code in both frontend and backend layers.
• Experience with AWS or equivalent cloud infrastructure and modern deployment practices.
• Experience building or deploying data pipelines or data engineering work.
• Strong product instincts — you think about the user, not just the code.
• Comfortable owning loosely-scoped problems and moving from ambiguity to shipped feature independently.
• Bachelor's degree in Computer Science or a related field.
• Bonus: experience with LLM integrations, agentic AI systems, or RAG architectures; background in enterprise SaaS, retail technology, or data-intensive products; familiarity with data visualization or streaming architectures.
Compensation & Benefits
Base salary range: $120,000 – $200,000 USD annually. Visa sponsorship is not available.
Location
On-site in New York, NY.
Originally posted on Himalayas