- Work directly with customers to understand their workflows, pain points, data environments, and operational constraints.
- Contribute to both the core platform and customer-specific integrations: build reusable capabilities into the product, then adapt and deploy them in each customer's environment.
- Build and deploy AI-enabled applications, agents, and workflow automation, applying AI/ML and LLM techniques such as RAG, guardrails, and evals to deliver reliable customer solutions.
- Translate customer needs into technical requirements, implementation plans, and product feedback for the core engineering team.
- Own delivery from prototype through production, including architecture, backend services, APIs, integrations, observability, testing, deployment, and customer acceptance.
- Integrate with customer systems, data sources, identity providers, and cloud or on-prem infrastructure.
- Partner with product, engineering, security, and customer teams to ensure solutions are secure, reliable, auditable, and operationally useful.
- Debug issues in deployed environments and drive fast resolution across application, infrastructure, data, and integration layers.
- Operate with strong judgment in environments involving sensitive data and business-critical workflows.
Requirements
- 8+ years of software engineering experience, with a strong foundation in building and shipping production-quality systems.
- Ability to apply AI and ML techniques, including LLM-based approaches such as RAG, guardrails, and evals, to real customer problems.
- Scalable system design experience, ensuring solutions scale reliably as usage, data, and complexity grow.
- Experience with backend engineering, distributed systems, APIs, data pipelines, cloud infrastructure, or applied AI/ML systems.
- Comfort working across the full stack when needed, including backend services, frontend interfaces, infrastructure, integrations, and deployment workflows.
- Ability to operate in ambiguous customer environments and turn unclear requirements into working software.
- Strong technical communication skills with engineers, product teams, executives, and customer stakeholders.
- High ownership, bias for action, and ability to drive outcomes without waiting for perfect requirements.
- Strong debugging instincts and ability to reason across application code, data, infrastructure, networking, and customer systems.
- Prior experience as a full-stack or backend software engineer, forward deployed engineer, solutions engineer, product engineer, platform engineer,, or founding/startup engineer.
Benefits
- Career track opportunity with potential for rapid advancement withstrong performanceas the firm grows
- 100% employer paid, comprehensive health care including medical, dental, and vision for you and your family.
- Paid maternity and paternity for 14 weeks at employees' normal pay.
- Unlimited PTO, with management approval.
- Opportunities for professional development and continued learning.
- Optional 401K, FSA, and equity incentives available.
- Mental health benefits are available through
- Tara Mind .
Core Competencies
Demonstrated expertise in software engineering with a focus on building and deploying AI-enabled applications and integrations. Proven ability to translate customer needs into technical solutions while ensuring system reliability, scalability, and security in complex environments.
Highest-signal resume keywords
- 8+ Years of Software Engineering Experience
- AI and ML Techniques Application
- Scalable System Design
- Backend Engineering and Distributed Systems
- Strong Technical Communication Skills
ATS Optimization Keywords
Hard Skills
- AI Techniques
- ML Techniques
- LLM-based Approaches
- Backend Engineering
- APIs
- Data Pipelines
- Cloud Infrastructure
- Full Stack Development
- Debugging
- System Design
Soft Skills
- Technical Communication
- High Ownership
- Bias for Action
- Problem-Solving
- Judgment in Sensitive Environments
Industry Keywords
- Production-quality Systems
- Customer Integrations
- Operational Constraints
- Workflow Automation
- Sensitive Data Management
Tools & Technologies
- Cloud Infrastructure
- Integration Systems
- Observability Tools
- Deployment Workflows
- Data Sources