Socure
digital economy
SeniorAIEngineer
“Senior AI Engineer at Socure. Skills: AI/ML, LLM, Python, agentic framework. Prioritize high-impact automation. Partner with business teams”
What You'll Achieve.
verify 100% of good identities in real time; stop fraud before it starts; deliver intelligent automation; drive step-function gains in efficiency, accuracy, and decision-making
Industry & Context.
think critically; operate in ambiguity; translate workflows into technical solutions; failure-mode analysis
What They're Looking For.
Must Have
8+ years of software engineering experience, at least 2 years focused on AI/ML systems or LLM-powered applications in production, Deep hands-on experience with LLM APIs, at least one agentic framework (e.g. LangGraph, CrewAI or AutoGen), Python skills, experience building production-grade backend services, APIs, and data pipelines, Proven ability to operate in ambiguity, Experience shipping AI/automation solutions that directly impacted business operations, systems thinking, Ability to collaborate directly with non-technical business stakeholders
Nice to Have
Experience with multi-agent systems, workflow orchestration, or complex tool-use patterns in production, Familiarity with evaluation frameworks (e.g., LangSmith, Weights & Biases, Arize, or custom eval pipelines) for AI systems, Experience with RAG pipelines, vector databases, knowledge graphs, or memory/grounding systems, Experience with real-time or streaming AI systems, Familiarity with AI safety and security practices, Background in a regulated industry (fintech, healthcare, government), Experience with agent skill abstraction and structured tool integration via MCP (Model Context Protocol), function calling or similar protocols, Experience with AWS-hosted LLM infrastructure (Bedrock, AgentCore/Strands, Lambda, SageMaker) or equivalent cloud ML services
What You'll Do.
Prioritize high-impact automation
Partner with business teams
Catalog manual workflows
Rank workflows by impact
Build multi-step agent workflows
Design planner–executor architectures
Develop stateful agent systems
Incorporate human-in-the-loop controls
Leverage Agentic AI Foundations platform
Provide feedback on platform priorities
Create differentiated internal solutions
Stay ahead of emerging AI technologies
Discover reusable agent design patterns
Contribute patterns to Agentic AI Foundations
Leverage evaluation harness
Leverage tracing substrate
Continuous performance assessment
Failure-mode analysis
Optimization of speed and accuracy
How You'll Work.
Team & Collaboration
Partner with business teams (e.g., Revenue Ops, Marketing, Finance Ops, Talent Acquisition); Collaborate directly with non-technical business stakeholders; Provide feedback that shapes platform priorities; Contribute reusable agent design patterns back to the Agentic AI Foundations paved paths
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