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Senior Java AI Engineer/Architect
Prophecy Technologies
6 hours ago
Full-time
On-site
Phoenix, Arizona, United States
Role Overview:
The Senior Java AI Engineer/Architect will own end-to-end architecture, from requirements and constraints through HLD/LLD, implementation, release, monitoring, and production improvement. This role involves designing and delivering secure, high-throughput REST APIs, microservices, and event-driven integrations using Java/Spring Boot, as well as developing production AI capabilities leveraging LLM APIs, RAG, vector search, and agents, with a focus on evaluation, guardrails, access controls, monitoring, and operational support.
Key Responsibilities: Own end-to-end architecture from requirements and constraints through HLD/LLD, implementation, release, monitoring and production improvement. Independently sketch and defend a distributed-system design; articulate assumptions, bottlenecks, trade-offs, alternatives and design decisions. Critically review architecture, identify security/scalability/consistency gaps and propose workable remediation with measurable impact. Document decisions as ADRs and explain personal design contributions, rejected alternatives and outcomes. Design and deliver secure, high-throughput REST APIs, microservices and event-driven integrations using Java/Spring Boot or comparable backend technologies. Engineer reliable financial workflows using idempotency keys, transactional boundaries, retries, reconciliation, auditability and controlled recovery from partial failures. Design appropriate data models, caching, message processing and fault-tolerant service interactions. Design and enforce fine-grained authorization at API, service and resource levels; distinguish authentication, token validation and authorization decisions. Apply OAuth2/OIDC, JWT, RBAC/ABAC, least privilege, secure service identity and tenant isolation, including authorization of AI tools and retrieved documents. Deliver production AI capabilities using LLM APIs, RAG, vector search and agents where appropriate; own evaluation, guardrails, access controls, monitoring and operational support. Explain why an AI architecture was selected, its limitations, security risks, fallback behavior and measurable business results. Deploy on AWS, Azure or GCP; use Docker/Kubernetes, automated CI/CD and infrastructure as code. Define SLOs, investigate latency/throughput issues, use metrics/logs/traces and lead root-cause analysis and resilience improvements. Communicate designs clearly in technical reviews and respond constructively to design challenges. Required Skills:
Independently design scalable, secure, highly available distributed systems from ambiguous requirements; produce HLD/LLD, API contracts, data models, sequence diagrams and ADRs. Explain trade-offs between synchronous/asynchronous communication, database technologies, caching, consistency, throughput, latency and operational cost. Identify flaws in a proposed design and propose practical corrections without extensive prompting; explain assumptions, alternatives and failure modes. Demonstrated personal ownership of at least one complex production system, including implementation, rollout and incident response. Microservices, REST APIs, Kafka or equivalent messaging; idempotency, retries, timeouts, circuit breakers, dead-letter queues, ordering, outbox/Saga patterns and transaction consistency. Authentication versus authorization (AuthN/AuthZ), OAuth2/OIDC, JWT validation, RBAC/ABAC, resource-level permissions, least privilege, tenant isolation and service-to-service security. Capacity planning, horizontal scaling, performance diagnosis, SLOs/SLIs, tracing, observability, failure recovery, safe deployment and rollback. Financial transaction or payments workflow design (ACH, push payments, P2P, settlement, reconciliation) strongly preferred. Strong backend programming and hands-on delivery (Java 17/21, Spring Boot, Spring Cloud, Hibernate/JPA preferred). Production AI/GenAI integration experience: LLM APIs, RAG, agent/tool orchestration, vector retrieval, evaluation, access control, prompt-injection safeguards and observability. SQL and NoSQL database design; cloud (AWS, Azure or GCP), Docker/Kubernetes, CI/CD and automated testing. Qualifications:
5-8 years of experience in system design, distributed systems, security, production engineering, and AI. Preferred Skills:
Kotlin/Python, LangChain/LlamaIndex, MCP, multi-agent systems, GraphRAG, knowledge graphs, MLOps/LLMOps, NVIDIA NIM, Terraform, GKE, Redis, MongoDB, PostgreSQL, DynamoDB and Snowflake. Senior technical leadership with demonstrable individual design ownership. Structured, concise communication of system diagrams, assumptions, risks, trade-offs and remediation options. Ability to reason independently under follow-up questions, acknowledge limitations and improve designs collaboratively. Mentoring, peer design reviews, cross-team influence, production accountability and stakeholder engagement.
The Senior Java AI Engineer/Architect will own end-to-end architecture, from requirements and constraints through HLD/LLD, implementation, release, monitoring, and production improvement. This role involves designing and delivering secure, high-throughput REST APIs, microservices, and event-driven integrations using Java/Spring Boot, as well as developing production AI capabilities leveraging LLM APIs, RAG, vector search, and agents, with a focus on evaluation, guardrails, access controls, monitoring, and operational support.
Key Responsibilities: Own end-to-end architecture from requirements and constraints through HLD/LLD, implementation, release, monitoring and production improvement. Independently sketch and defend a distributed-system design; articulate assumptions, bottlenecks, trade-offs, alternatives and design decisions. Critically review architecture, identify security/scalability/consistency gaps and propose workable remediation with measurable impact. Document decisions as ADRs and explain personal design contributions, rejected alternatives and outcomes. Design and deliver secure, high-throughput REST APIs, microservices and event-driven integrations using Java/Spring Boot or comparable backend technologies. Engineer reliable financial workflows using idempotency keys, transactional boundaries, retries, reconciliation, auditability and controlled recovery from partial failures. Design appropriate data models, caching, message processing and fault-tolerant service interactions. Design and enforce fine-grained authorization at API, service and resource levels; distinguish authentication, token validation and authorization decisions. Apply OAuth2/OIDC, JWT, RBAC/ABAC, least privilege, secure service identity and tenant isolation, including authorization of AI tools and retrieved documents. Deliver production AI capabilities using LLM APIs, RAG, vector search and agents where appropriate; own evaluation, guardrails, access controls, monitoring and operational support. Explain why an AI architecture was selected, its limitations, security risks, fallback behavior and measurable business results. Deploy on AWS, Azure or GCP; use Docker/Kubernetes, automated CI/CD and infrastructure as code. Define SLOs, investigate latency/throughput issues, use metrics/logs/traces and lead root-cause analysis and resilience improvements. Communicate designs clearly in technical reviews and respond constructively to design challenges. Required Skills:
Independently design scalable, secure, highly available distributed systems from ambiguous requirements; produce HLD/LLD, API contracts, data models, sequence diagrams and ADRs. Explain trade-offs between synchronous/asynchronous communication, database technologies, caching, consistency, throughput, latency and operational cost. Identify flaws in a proposed design and propose practical corrections without extensive prompting; explain assumptions, alternatives and failure modes. Demonstrated personal ownership of at least one complex production system, including implementation, rollout and incident response. Microservices, REST APIs, Kafka or equivalent messaging; idempotency, retries, timeouts, circuit breakers, dead-letter queues, ordering, outbox/Saga patterns and transaction consistency. Authentication versus authorization (AuthN/AuthZ), OAuth2/OIDC, JWT validation, RBAC/ABAC, resource-level permissions, least privilege, tenant isolation and service-to-service security. Capacity planning, horizontal scaling, performance diagnosis, SLOs/SLIs, tracing, observability, failure recovery, safe deployment and rollback. Financial transaction or payments workflow design (ACH, push payments, P2P, settlement, reconciliation) strongly preferred. Strong backend programming and hands-on delivery (Java 17/21, Spring Boot, Spring Cloud, Hibernate/JPA preferred). Production AI/GenAI integration experience: LLM APIs, RAG, agent/tool orchestration, vector retrieval, evaluation, access control, prompt-injection safeguards and observability. SQL and NoSQL database design; cloud (AWS, Azure or GCP), Docker/Kubernetes, CI/CD and automated testing. Qualifications:
5-8 years of experience in system design, distributed systems, security, production engineering, and AI. Preferred Skills:
Kotlin/Python, LangChain/LlamaIndex, MCP, multi-agent systems, GraphRAG, knowledge graphs, MLOps/LLMOps, NVIDIA NIM, Terraform, GKE, Redis, MongoDB, PostgreSQL, DynamoDB and Snowflake. Senior technical leadership with demonstrable individual design ownership. Structured, concise communication of system diagrams, assumptions, risks, trade-offs and remediation options. Ability to reason independently under follow-up questions, acknowledge limitations and improve designs collaboratively. Mentoring, peer design reviews, cross-team influence, production accountability and stakeholder engagement.