Staff Software Engineer (AI/ML)

Location: Hybrid at hirify.global hubs in San Francisco, New York, or Seattle, United States

Salary: $225K–$280K annually, plus equity and bonus.

Company

hirify.global builds identity trust infrastructure for the digital economy, including real-time identity verification and fraud prevention systems.

What you will do

• Design, implement, test, and operate backend services for agent orchestration, asynchronous workflows, state management, model integration, and risk investigations.
• Build agent frameworks, developer tooling, secure connectors, tool execution, memory, human review, and policy-controlled workflows.
• Develop knowledge-ingestion, enrichment, retrieval, and knowledge-graph capabilities across structured data, unstructured documents, search systems, vector stores, and APIs.
• Integrate and optimize machine-learning models, model routing, inference, caching, batching, retrieval, context construction, and prompt workflows.
• Build evaluation, regression testing, observability, telemetry, and operational processes for reliable AI systems, including on-call and incident response.
• Write technical designs, review code and architecture, and collaborate with Product, Fraud and Risk, Investigation Operations, Platform Engineering, SRE, Security, Privacy, and Data Science.

Requirements

• Bachelor’s or master’s degree in Computer Science, Engineering, or a related technical field, or equivalent practical experience.
• Professional experience building software or backend services from implementation through testing and production operation.
• Backend development experience with API design, service-oriented architecture, asynchronous programming, testing, debugging, performance optimization, and a backend or data-intensive language such as Python, Java, Go, or TypeScript.
• Understanding of distributed systems, including queues, retries, idempotency, timeouts, concurrency, partial failures, and service reliability.
• Experience building applications with large language models, AI agents, tool calling, retrieval-augmented generation, structured generation, or related generative-AI technologies.
• Understanding of agent architecture, including orchestration, state transitions, task execution, tool use, context management, memory, human escalation, and observability.
• Experience grounding AI or agent workflows with domain knowledge, entity context, policies, case history, live data, or model outputs; and practical knowledge of embeddings, vector and lexical search, metadata filtering, hybrid retrieval, reranking, query expansion, or multi-stage retrieval.
• Experience with knowledge graphs, graph databases, entity resolution, ontology or schema design, provenance, temporal data modeling, and combining structured data, documents, search, vector retrieval, and live APIs.
• Working knowledge of machine learning and experience supporting datasets, labeling, training, fine-tuning, experiment tracking, evaluation, versioning, deployment, monitoring, model optimization, and AI/ML system quality.
• Experience with cloud infrastructure and containers, preferably AWS and Kubernetes, plus several of relational databases, queues or event streams, object storage, caching, search, vector or graph databases, and observability platforms.
• Understanding of authentication, authorization, secrets management, tenant isolation, data protection, privacy-sensitive design, and maintainable, well-tested code.
• Ability to break down problems, estimate work, identify dependencies and risks, deliver with appropriate guidance, communicate clearly, and collaborate across engineering, product, data science, and operations.
• Startup DNA required: ability to thrive in fast-moving, high-ambiguity environments and take ownership like a founder.

Nice to have

• Experience applying AI or machine learning to fraud, identity, financial crime, compliance, trust and safety, investigations, or other regulated domains.
• Experience with agent frameworks, model gateways, evaluation and tracing platforms, GraphRAG, enterprise search, MCP-style connectors, or custom orchestration systems.
• Experience with AWS Bedrock, SageMaker, EKS, vLLM, GPU-backed inference, fine-tuned or domain-specific models, workflow engines, durable execution, or distributed task processing.
• Experience with Neo4j, Neptune, OpenSearch, Elasticsearch, or comparable graph and search technologies.
• Experience with data enrichment, entity resolution, semantic search, knowledge platforms, retrieval-augmented applications, model monitoring, drift detection, governance, or responsible AI.
• Contributions to reusable libraries, technical documentation, testing frameworks, architecture patterns, or engineering practices.

Culture & Benefits

• Full-time employment in a fast-moving environment with broad technical ownership and complex customer-impacting problems.
• Hybrid work through hirify.global hubs in the United States.
• Equity and bonus are offered in addition to the stated salary.
• hirify.global is an equal opportunity employer and provides accommodation support during hiring and onboarding when requested.