Senior Software Engineering - Machine Learning

Forward is scaling fast, and we need senior engineers who can grow with the platform — not just build features, but harden, secure, and extend the system. This role is a core contributor on our engineering team. You'll ship full-stack product work, build agentic AI systems that automate complex workflows, and own meaningful parts of the platform as we scale it from where it is today to where it needs to be.

You will work cross-functionally with product, design, and engineering leadership to translate ambiguous business problems into well-scoped technical solutions. Key Responsibilities Architect, build, and maintain full-stack applications using TypeScript, Next.js, React, and Node.js across our product surface area.

Own end-to-end feature delivery from database schema and API design through frontend UI/UX, including observability, testing, and deployment.

Agentic AI & LLM Integration Design and implement agentic AI systems — autonomous agents that plan multi-step workflows, use tools, call APIs, and make decisions with minimal human oversight.

Stand up and evolve AI platform infrastructure as the roadmap matures — model serving, orchestration, and evaluation pipelines.

Streaming & Real-Time Data Build and operate real-time streaming data pipelines using Kafka (or Kafka-compatible platforms like WarpStream), stream processors, and event-driven architectures.

Design event-driven data flows that feed both product and AI systems with low-latency data.

Tune Kafka performance, partitioning strategies, and consumer groups for throughput and reliability.

Contribute to scaling the platform from current load to the next order of magnitude — capacity planning, performance tuning, and resilience engineering.

Build and harden security-critical paths: authentication, authorization, secrets management, encryption, and data isolation.

Improve operational maturity — observability, alerting, incident response, and on-call practices that keep a payments platform reliable.

Help advance compliance posture (PCI DSS, SOC 2) by building the controls, audit trails, and tooling regulated environments require.

You default to shipping, documenting, and iterating

Required Qualifications 7+ years of professional software engineering experience building and shipping production systems at scale.

Track record of leading small engineering teams while staying hands-on — you're a player-coach, not a meeting machine.

Demonstrated experience building agentic AI systems — autonomous agents, multi-step tool-use workflows, LLM orchestration, or AI-driven automation pipelines.

Solid understanding of relational databases (PostgreSQL), NoSQL (DynamoDB), and data modeling for high-throughput transactional systems.

Experience with cloud infrastructure (AWS preferred) — EKS/Kubernetes, Lambda, API Gateway, IAM, and infrastructure-as-code (Terraform, Pulumi, or CDK).

Experience building systems from scratch — not just maintaining what exists.

js (App Router, Server Components, API routes, middleware, ISR/SSR strategies).

Hands-on experience with Apache Kafka or Kafka-compatible streaming platforms (producers, consumers, exactly-once semantics, schema registries, stream processing).

Familiarity with modern AI/ML tooling — LangChain, LlamaIndex, OpenAI/Anthropic APIs, vector databases, embedding pipelines.

Background with data infrastructure components like Apache Iceberg, StarRocks, ClickHouse, or RisingWave.

Service mesh with GitOps-driven rollouts (Argo/Flux) — canary deployments, traffic shaping.

Contributions to open-source projects or technical blog posts demonstrating thought leadership.

What We Offer Competitive salary and equity package.

Flexible work arrangements and generous PTO.

The opportunity to shape both the AI roadmap and the platform that powers it.