Senior Software Engineer – Backend Platforms and Agentic & ML Systems at Socure · LumiJobs

Responsibilities

A key part of the role is helping agents work with accurate, relevant, and timely domain knowledge. You will build capabilities that dynamically provide contextual information to agents, combine structured and unstructured data, support knowledge-graph and retrieval workflows, and preserve evidence and provenance for downstream decisions.
Job Responsibilities
Design, implement, test, and operate backend services that support agent orchestration, task execution, state management, model integrations, and investigation workflows.
Build synchronous and asynchronous workflows for agent tasks, including queues, retries, resumability, cancellation, idempotency, scheduling, and failure recovery.
Contribute to agent frameworks and developer harnesses that support tool calling, structured outputs, reusable skills, actor-based workflows, human review, and policy-controlled execution.
Implement services that dynamically inject relevant knowledge into agent workflows based on investigation type, entity context, workflow state, customer policy, prior findings, and current task requirements.
Build domain-grounding capabilities that help agents distinguish authoritative facts, customer-defined policies, derived signals, hypotheses, and unverified observations.
Develop knowledge-ingestion and enrichment pipelines that normalize, classify, chunk, index, version, and refresh structured and unstructured data.
Implement retrieval workflows using combinations of semantic search, lexical search, metadata filtering, hybrid retrieval, reranking, entity-aware retrieval, and temporal filtering.
Contribute to knowledge-graph systems that represent entities, relationships, events, evidence, provenance, and risk signals.
Support graph traversal, multi-hop retrieval, graph-enhanced context assembly, and integration between graph, vector, search, document, and API-based data sources.
Implement context-selection logic that balances relevance, freshness, source authority, latency, tenant permissions, and model context limits.

Qualification

Experience with backend developmentUnderstanding of agent architectureExperience building backend servicesExperience combining structured dataExperience with agent frameworksExperience with AWS BedrockExperience with workflow enginesExperience with model monitoring

Required

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, including experience taking features from implementation through testing and production operation.
Experience with backend development, API design, service-oriented architectures, asynchronous programming, testing, debugging, and performance optimization.
Understanding of distributed-system concepts such as queues, retries, idempotency, timeouts, concurrency, partial failures, and service reliability.
Experience with a programming language used for backend or data-intensive systems, such as Python, Java, Go, TypeScript, or a comparable language.
Experience building applications that use 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 building backend services, agent components, developer tooling, data pipelines, or other reusable platform capabilities.
Experience grounding AI or agent workflows with domain knowledge, entity context, customer policies, case history, live data, model outputs, or other task-relevant information.
Practical understanding of retrieval concepts such as embeddings, vector search, lexical search, metadata filtering, hybrid retrieval, reranking, query expansion, or multi-stage retrieval.
Experience with one or more of the following: knowledge graphs, graph databases, entity graphs, graph traversal, graph-enhanced retrieval, entity resolution, ontology or schema design, provenance, or temporal data modeling.
Experience combining structured data, unstructured documents, search systems, vector retrieval, and live API-based data sources.

Preferred

Experience building AI or machine-learning systems for 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, or comparable technologies.
Experience deploying fine-tuned or domain-specific models alongside larger managed models.
Experience with workflow engines, durable execution, distributed task processing, or long-running job orchestration.
Experience with graph databases or graph-processing technologies such as Neo4j, Neptune, OpenSearch, Elasticsearch, or comparable systems.
Experience building data-enrichment pipelines, entity-resolution systems, semantic search, knowledge platforms, or retrieval-augmented applications.
Experience with model monitoring, feature and data drift detection, experiment tracking, model governance, or responsible AI practices.

Senior Software Engineer – Backend Platforms and Agentic & ML Systems

Responsibilities

Qualification

Required

Preferred

Company

Socure

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