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About the Company
We’re looking for a Junior & Senior AI Engineer to design, build, and ship production-grade Generative AI applications at medium-to-large scale. You’ll own end-to-end delivery—from model selection and evaluation to robust deployment, monitoring, and continuous improvement. You’ll operate with minimal hand-holding, mentor junior engineers, and collaborate cross-functionally to deliver measurable business impact.
About the Role
What You’ll Do
- Build and ship GenAI applications: Develop, deploy, and maintain production-grade GenAI-powered systems (e.g., RAG, agents, copilots, content intelligence, workflow automation).
- Design and deliver agentic systems: Architect and implement agentic workflows (tool use/function calling, planning, memory, reflection/verification loops, multi-agent coordination) to automate complex tasks with reliability and guardrails.
- Own architecture & scalability: Design reliable, secure, cost-efficient architectures that scale (batch + real-time), including latency optimization and throughput planning.
- Model + tooling expertise: Select and integrate appropriate LLMs and GenAI tools (open-source and/or hosted), including embeddings, rerankers, multimodal models, and prompt/agent frameworks.
- Evaluation & quality: Create evaluation harnesses for accuracy, relevancy, safety, and hallucination reduction; implement offline/online testing and A/B experimentation.
- Data & retrieval systems: Design retrieval strategies, build indexing pipelines, optimize chunking, metadata strategies, vector databases/search, and caching.
- LLMOps / MLOps: Implement CI/CD for AI systems, model/version management, prompt and configuration management, automated testing, monitoring, alerting, and rollback strategies.
- Security & governance: Apply best practices for data privacy, PII handling, access controls, audit logging, content filtering, and policy compliance.
- Mentor and lead: Coach junior engineers through code reviews, pairing, and technical design; establish patterns and standards for AI engineering.
- Collaborate and influence: Partner with Product, Design, Data, and Platform teams to define requirements, milestones, and success metrics.
Responsibilities
- 1 to 3 Junior and 3-6 + years of software engineering experience, with 3+ years building ML/AI systems, and significant hands-on work in Generative AI.
- Demonstrated experience delivering production-grade GenAI applications at medium-to-large scale (reliability, performance, observability, cost controls).
- Agentic systems expertise: Proven experience building and deploying agentic systems in production, including tool/function calling, orchestration, state management, guardrails, and robust handling of failures/timeouts.
- Strong programming skills in Python (and/or TypeScript/Java/Go), including writing clean, maintainable, well-tested code.
- Proven experience with:
- LLMs (hosted and/or open-source), prompt engineering, structured outputs, and tool use
- RAG pipelines, embeddings, reranking, retrieval optimization, and vector search
- Distributed systems (REST/gRPC), async processing, queues, caching, rate limiting
- Cloud platforms (AWS/GCP/Azure) and containerization (Docker/Kubernetes)
- Monitoring and evaluation for GenAI (quality metrics, drift, safety, latency, cost)
- Ability to work independently, take ownership, and drive projects forward with minimal oversight.
- Track record of mentoring junior engineers and collaborating effectively across teams.
Qualifications
- Experience fine-tuning or adapting models (LoRA/PEFT), and working with multi-modal use cases.
- Familiarity with common GenAI stacks: orchestration frameworks, vector DBs, observability tools, feature flags, and experimentation platforms.
- Background in security/privacy by design (SOC2/HIPAA/PII concerns, depending on domain).
- Experience leading technical roadmaps and influencing architecture across teams.
Required Skills
- A go-getter: You spot opportunities, propose solutions, and move from idea → prototype → production.
- Hands-on and pragmatic: You balance quality and speed, and know when to iterate vs. harden.
- A strong communicator: You explain tradeoffs clearly and align stakeholders.
- A team player: You elevate the group, collaborate openly, and mentor junior teammates.
- Outcome-driven: You care about impact—accuracy, user experience, reliability, and cost.
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