Forward Deployed Software Engineer, Agentic AI

About Eranova

Eranova’s platform automates enterprise workflows through AI agents, unlocking value that traditional software couldn’t reach. The modules within our suite leverage Agentic AI to automate back-office processes across industries at enterprise-scale.

Eranova is seeking talented and eager team members interested in contributing to real-world applications of AI and excited to define the standard for how AI Agents integrate into enterprise workflows.

Our Forward Deployed Engineering team works in a high-ownership, fast-moving, high-accountability environment. We provide opportunities for entry level through lead engineers to drive real impact and own major deployments at a company carving the way for enterprise applications of AI Agents.

https://www.eranova.ai

Role Note

This role is designed for an exceptional software engineer first — someone who writes clean, modular, object-oriented code with hands-on experience architecting and deploying scalable systems on AWS. Candidates with backgrounds focused primarily on data science, analytics, or model experimentation without strong engineering and system-design expertise will not be a fit for this position.

Familiarity with the Agentic AI stack and experience applying AI agents to enterprise workflows are highly valued, but secondary to your ability to design, build, and ship robust software systems.

Traits that matter in this role

• This is a role for engineers who want direct ownership, real customer exposure, and the opportunity to shape the future of enterprise Agentic AI.
• You are highly technical and highly practical
• You can move from whiteboarding a workflow with a customer to implementing the production system behind it
• You are comfortable owning ambiguous problems end to end
• You write code with clarity and discipline
• You can communicate clearly with both engineers and non-technical stakeholders
• You thrive in high-accountability environments where speed and quality both matter
• You are energized by seeing software deployed in real operational settings with real business impact

Responsibilities

• Own customer deployments from initial discovery through launch and ongoing iteration
• Travel onsite to work directly with client stakeholders, workshop workflows, and gather technical and operational requirements
• Map back-office processes and identify how AI agents can automate high-value operational tasks
• Assess and integrate with enterprise systems such as ERP, TMS, accounting platforms, document systems, and internal operational tools
• Design and build production-grade backend systems that support enterprise AI workflows
• Architect and deploy cloud infrastructure on AWS using infrastructure-as-code, including CloudFormation-based environments and supporting services
• Build and maintain services using core AWS components such as Lambda, S3, SQS, DynamoDB, API Gateway, EC2, and RDS/SQL-based systems where appropriate
• Design secure, scalable, and maintainable system architectures for enterprise deployments
• Implement agentic AI components including LLM-powered workflows, structured outputs, retrieval patterns, and orchestration logic where appropriate
• Write clean, modular, understandable object-oriented code that other engineers can easily maintain and extend
• Partner closely with internal engineering and product teams to improve reusable deployment patterns, tooling, and architecture
• Support critical deployment phases with urgency and strong execution standards
• Serve as a highly credible technical partner to client stakeholders throughout implementation

Qualifications

• Strong software engineering foundation with proven experience building and deploying production-grade systems
• Hands-on experience architecting and deploying applications on AWS in real production environments
• Strong proficiency in Python for backend application development
• Demonstrated experience writing clean, modular, maintainable object-oriented code
• Strong understanding of software design, system architecture, reliability, and engineering best practices
• Experience deploying enterprise-ready systems with a high bar for stability, readability, and maintainability
• Experience working with AWS services such as Lambda, S3, SQS, DynamoDB, API Gateway, EC2, and relational databases
• Experience with infrastructure-as-code, especially AWS CloudFormation
• Strong experience with SQL and relational databases
• Ability to deeply understand and explain systems you have built, including architecture decisions, tradeoffs, and implementation details
• Strong communication skills and comfort working directly with external stakeholders
• Willingness to travel up to 50% for client implementations
• Willingness to work onsite in Charlotte, North Carolina
• Experience architecting end-to-end serverless systems on AWS
• Experience integrating with enterprise platforms such as ERP, TMS, accounting, and other operational systems
• Experience building software for document-heavy or workflow-heavy enterprise environments
• Experience applying AI agents to real business processes, especially automation of enterprise workflows
• Experience with structured outputs for LLM applications
• Experience with retrieval-augmented generation, embeddings, and related AI application patterns
• Experience building and maintaining CI/CD pipelines, including GitHub Actions
• Familiarity with frontend technologies such as React, TypeScript, Next.js, and Tailwind CSS
• Experience operating in highly ambiguous, fast-moving client environments