What you’ll do
Design, build, and maintain backend services in Python, including REST/GraphQL APIs and integrations with internal and external systems.
Implement and integrate AI/LLM-powered workflows (e.g., RAG, agentic workflows, orchestration, prompt/guardrail patterns).
Work across our agentic platform stack to connect services, tools, and data sources into reliable, observable workflows.
Translate UX designs and design systems into clean, maintainable frontend code (React), wiring up APIs, state, and components.
Collaborate with product, UX, and other engineers to break down requirements, estimate work, and deliver in iterative increments.
Write readable, testable code with appropriate unit/integration tests and participate in code reviews.
Help ensure engineering standards, tooling, and CI/CD practices for secure, scalable AI workloads.
Diagnose and resolve issues across the stack (backend, integrations, and frontend behavior).
Use agentic development for rapid quality code and be excited about staying at the forefront of AI skills.
Core skills & experience
4+ years of software engineering experience, with significant time in Python building production services.
Hands-on experience integrating with LLMs or AI services (e.g., AWS Bedrock, OpenAI, Anthropic, LangChain, AgentCore, or similar).
Strong experience with API design and implementation (REST/JSON; GraphQL a plus).
Solid understanding of data modeling, persistence, and integration (SQL/NoSQL, queues, event-driven patterns, etc.).
Working proficiency with modern frontend frameworks (React preferred; Vue/Angular acceptable with willingness to work in React).
Ability to take Figma/wireframes/design specs and implement responsive, accessible UI using a component library / design system (e.g., Tailwind + component kits).
Experience with cloud-native development on at least one major cloud (AWS preferred) and containerization/orchestration concepts.
Familiarity with secure coding practices, authentication/authorization patterns (OAuth/OIDC, RBAC), and observability (logging, metrics, tracing).
Comfortable working in an agile environment with iterative delivery, backlog tracking (e.g., Jira), and collaboration tools.
Experience building or integrating with agentic AI workflows (multi-agent graphs, tools, guardrails, human-in-the-loop flows).
Knowledge of event-driven architectures, message buses, and workflow engines.
Experience with infrastructure-as-code (Terraform, CloudFormation) and CI/CD in cloud environments.
Background working on platform or shared services used by multiple product teams.
Familiarity with design systems and reusable UI component libraries (e.g., shadcn, Material).
Must have
Nice to have
What success looks like in this role
You can own a feature end to end: from API design and AI integration through to a functional UI, without heavy supervision on the frontend.
You move quickly but safely, shipping incremental value while maintaining code quality, reliability, and security.
You collaborate well with product, UX, and other engineers, and you’re comfortable operating in an evolving Enterprise AI platform context.
Skills Required
- 4+ years of software engineering experience with significant time in Python building production services
- Hands-on experience integrating with LLMs or AI services (e.g., AWS Bedrock, OpenAI, Anthropic, LangChain, AgentCore)
- Strong experience with API design and implementation (REST/JSON; GraphQL a plus)
- Understanding of data modeling, persistence, and integration (SQL/NoSQL, queues, event-driven patterns)
- Working proficiency with modern frontend frameworks (React preferred; Vue/Angular acceptable)
- Ability to implement responsive, accessible UI from Figma/wireframes using a component library/design system (e.g., Tailwind + component kits)
- Experience with cloud-native development on at least one major cloud (AWS preferred) and containerization/orchestration concepts
- Familiarity with secure coding practices and authentication/authorization patterns (OAuth/OIDC, RBAC) and observability (logging, metrics, tracing)
- Comfortable working in an agile environment with backlog tracking (e.g., Jira) and collaboration tools
- Write readable, testable code with appropriate unit/integration tests and participate in code reviews
- Experience building or integrating with agentic AI workflows (multi-agent graphs, tools, guardrails, HIL flows)
- Knowledge of event-driven architectures, message buses, and workflow engines
- Experience with infrastructure-as-code (Terraform, CloudFormation) and CI/CD in cloud environments
- Background working on platform or shared services used by multiple product teams
- Familiarity with design systems and reusable UI component libraries (e.g., shadcn, Material)
AHEAD Compensation & Benefits Highlights
The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about AHEAD and has not been reviewed or approved by AHEAD.
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Retirement Support — 401(k) contributions are matched dollar-for-dollar on the first $5,000 each year, with matching made each pay period and immediate 100% vesting. This structure signals above-standard employer support for retirement savings.
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Affordable Benefits — Medical options include low employee premiums for PPO and HDHP plans, and the HDHP adds employer HSA funding plus a dollar-for-dollar HSA match up to stated amounts. Dental and vision plans list very low per-paycheck costs, helping keep overall healthcare spend manageable.
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Wellbeing & Lifestyle Benefits — No-cost telemedicine (including virtual mental health when enrolled), free Calm access for the employee and dependents, and an EAP with counseling are included. Company-paid life and disability plus voluntary protections (legal/ID, pet insurance) and other extras round out a comprehensive set of supports.
AHEAD Insights
What We Do
AHEAD builds platforms for digital business. By weaving together cloud infrastructure, intelligent operations, and modern applications, we help enterprises deliver on the promise of digital transformation.
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