- Company Name
- Reward Gateway
- Job Title
- AI Engineer
- Job Description
-
Job Title: AI Engineer
Role Summary: Design, develop, and ship production‑ready AI solutions that integrate LLMs, RAG, and agentic workflows into Reward Gateway’s platform. Own cloud infrastructure, monitoring, cost control, and ensuring responsible AI practices while collaborating cross‑functionally on product and engineering initiatives.
Expectations: Deliver resilient, scalable AI services; maintain high code quality and observability; adhere to privacy and regulatory standards; mentor peers and drive internal AI tooling improvements; iterate rapidly using data‑driven experiments and A/B testing.
Key Responsibilities
- Build and deploy AI and generative AI systems using LLMs, RAG, and agentic techniques.
- Accelerate development with AI coding assistants (Cursor, Copilot, Claude Code) and document repeatable patterns.
- Manage AWS/Kubernetes infrastructure, CI/CD pipelines, Terraform, monitoring, performance tuning, and cost optimization.
- Develop backend services in Python; contribute to React, TypeScript, PHP/MV frameworks as needed.
- Define and track offline/online metrics, conduct A/B tests, meet latency/cost targets, implement human‑in‑the‑loop validation, ensure robust observability.
- Implement retrieval pipelines (embeddings, vector DBs, hybrid search, chunking).
- Collaborate with Product using a working‑backward approach to create technical designs and iterative delivery.
- Improve shared AI tools, SDKs, reference implementations for RAG, tracing, prompt management, evaluation.
- Partner with Security, Legal, Data to establish AI policies, risk reviews, privacy, PII protection, regulatory compliance.
- Conduct code reviews, mentor peers, share knowledge to elevate engineering standards.
Required Skills
- Production‑grade AI delivery experience with LLMs, RAG, agentic workflows, prompt engineering, embeddings, vector stores, hybrid search.
- Strong Python programming, solid testing and CI/CD expertise; capability in React, TypeScript, PHP, or Node.js.
- Cloud and platform engineering: AWS, Kubernetes, Docker, IaC, Terraform, observability tools.
- Hands‑on with lead LLM providers (Anthropic, Claude, OpenAI); evaluate alternative models.
- Familiar with LLM ecosystems (LangChain, LlamaIndex), agentic frameworks, tracing, logging, prompt management, evaluation tools.
- Data engineering: dataset creation/validation, ETL, SQL schema design, model and product metrics definition & tracking.
- ML fundamentals: metric design, error analysis, model selection, performance tuning.
- Security and governance mindset, excellent communication with technical and non‑technical stakeholders, ownership from discovery to production and iteration.
Required Education & Certifications
- Bachelor’s degree in Computer Science, Engineering, or related field, or equivalent professional experience.
- Relevant certifications in cloud (e.g., AWS, Kubernetes) or AI/ML preferred but not mandatory.