Related skills
java python kubernetes go sparkπ Description
- Architect and code multi-agent systems that can reason, use tools, and execute end-to-end business processes (e.g., automated financial reconciliation, legal contract analysis, or supply chain demand forecasting)
- Partner with leaders in Finance, Marketing, Legal, and HR to translate their complex operational challenges into concrete AI architectures
- Evaluate the latest agentic frameworks and LLM providers to decide when to leverage third-party tools and when to build proprietary enterprise solutions
- Design highly available inference services and manage model serving at scale, ensuring these agents integrate seamlessly with existing corporate service meshes
- Implement "Security by Design," creating automated guardrails for PII/PHI filtering and mitigating prompt injection to ensure enterprise data remains secure
- Optimize the "Total Cost of Ownership" by managing trade-offs between agent reasoning depth (latency) and compute costs through intelligent caching and specialized routing
π― Requirements
- 8β10+ years in software engineering, with at least 2 years of deep focus on AI/ML infrastructure or data engineering at scale
- Mastery of Python, Go, or Java/Scala, with a strong grasp of distributed systems and microservices
- Proven experience with LLM orchestration frameworks (e.g., LangChain, LlamaIndex) and deep understanding of vector databases (e.g., Pinecone, Milvus, Weaviate)
- Hands-on experience with modern data stacks (Spark, Kafka, Snowflake, Databricks) and cloud environments (AWS, GCP, or Azure)
- Expert knowledge of Kubernetes, Docker, and CI/CD patterns specifically for machine learning lifecycles
π Benefits
- Medical, dental and vision insurance
- Generous paid time off policy
- Short-term and long-term disability
- Access to mental health services
- 401k, tuition reimbursement and student loan paydown plans
- Employee Stock Purchase Plan
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