Senior Applied AI Engineer – Agentic Systems
Contract W2
12 Months
No Travel Required
On-site
$60/hr
EL-Shaddai Technologies Inc
Fitment
Dice Job Match Score™
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Job Details
Skills
- EAS — autonomous workflow agents
- tool-calling loops
- Testing
- EAS
- backend orchestration
- API integration
- front-end
- RAG
- guardrails
- fallback logic
- escalation patterns
- tracing
- monitoring
- API
- TypeScript
- Orchestration
- LangGraph
- Anthropic SDK
- CrewAI
- AutoGen
- tool registries
- failure handling
- Python
- Artificial Intelligence
- QuickBooks
- Design Patterns
- SDK
- OpenAI
Summary
Agentic Feature Development & Full Stack Delivery
• Design, build, and ship agentic features directly within EAS — autonomous workflow agents, multi-step task orchestration, tool-calling loops, and human-in-the-loop interaction patterns
• Own agentic features end to end — from architecture and implementation through testing, hardening, and production deployment
• Identify high-value automation opportunities within EAS workflows and translate them into well-scoped, shippable features
• Integrate new agentic capabilities cleanly into an existing product codebase without disrupting existing functionality
• Own the full stack of agentic feature delivery — backend orchestration, API integration, and front-end surfaces that expose agent capabilities to enterprise users
• Build RAG pipelines over structured and unstructured data to power intelligent retrieval, decision support, and workflow automation within EAS
• Build memory and state management systems that allow agents to maintain context across multi-step, long-running workflows
Agentic AI — Core Requirement
• Build production-grade agentic systems with the reliability, observability, and failure handling that enterprise software demands
• Design evaluation harnesses to continuously test agent accuracy, behavioural consistency, and edge case handling
• Build guardrails, fallback logic, and escalation patterns that ensure agents degrade gracefully and keep users in control
• Instrument agentic features with logging, tracing, and monitoring to observe agent behaviour in production and iterate with confidence
• Participate in architecture and design reviews — contributing agentic expertise and maintaining quality standards across short delivery cycles
• Contribute to shared agentic patterns and reusable components that raise the capability baseline for the broader EAS engineering team
• Define and implement evaluation frameworks to measure agent accuracy, task completion, and behavioural consistency across diverse inputs and edge cases
• Experience with both automated eval pipelines (unit-level tool call testing, end-to-end trace evaluation) and human-in-the-loop review workflows for validating agent outputs in production
Required Experience
• Demonstrated hands-on experience building agentic AI capabilities inside a product — multi-step orchestration, tool-calling agents, memory systems, and human-in-the-loop flows used by real users in production
• Deep familiarity with agent frameworks — LangGraph, Anthropic SDK, OpenAI Agents SDK, CrewAI, AutoGen, or similar — applied in product feature delivery, not research
• Strong understanding of agentic design patterns: planning loops, tool registries, context window management, agent state machines, and failure handling
• Experience building and integrating RAG pipelines into product workflows
• Experience building production guardrails and evaluation frameworks for agentic features
• Strong full-stack engineering skills with production experience in Python and/or TypeScript
• 5+ years of full-stack software engineering with a strong shipping record
• 1+ years of hands-on experience building agentic AI features in production products
Preferred
• Experience integrating agentic capabilities into SaaS or fintech products at scale
• Familiarity with Intuit''''''''''''''''s developer platform or QuickBooks APIs
• Exposure to regulated or high-accuracy domains where agent reliability and auditability are non-negotiable
• Design, build, and ship agentic features directly within EAS — autonomous workflow agents, multi-step task orchestration, tool-calling loops, and human-in-the-loop interaction patterns
• Own agentic features end to end — from architecture and implementation through testing, hardening, and production deployment
• Identify high-value automation opportunities within EAS workflows and translate them into well-scoped, shippable features
• Integrate new agentic capabilities cleanly into an existing product codebase without disrupting existing functionality
• Own the full stack of agentic feature delivery — backend orchestration, API integration, and front-end surfaces that expose agent capabilities to enterprise users
• Build RAG pipelines over structured and unstructured data to power intelligent retrieval, decision support, and workflow automation within EAS
• Build memory and state management systems that allow agents to maintain context across multi-step, long-running workflows
Agentic AI — Core Requirement
• Build production-grade agentic systems with the reliability, observability, and failure handling that enterprise software demands
• Design evaluation harnesses to continuously test agent accuracy, behavioural consistency, and edge case handling
• Build guardrails, fallback logic, and escalation patterns that ensure agents degrade gracefully and keep users in control
• Instrument agentic features with logging, tracing, and monitoring to observe agent behaviour in production and iterate with confidence
• Participate in architecture and design reviews — contributing agentic expertise and maintaining quality standards across short delivery cycles
• Contribute to shared agentic patterns and reusable components that raise the capability baseline for the broader EAS engineering team
• Define and implement evaluation frameworks to measure agent accuracy, task completion, and behavioural consistency across diverse inputs and edge cases
• Experience with both automated eval pipelines (unit-level tool call testing, end-to-end trace evaluation) and human-in-the-loop review workflows for validating agent outputs in production
Required Experience
• Demonstrated hands-on experience building agentic AI capabilities inside a product — multi-step orchestration, tool-calling agents, memory systems, and human-in-the-loop flows used by real users in production
• Deep familiarity with agent frameworks — LangGraph, Anthropic SDK, OpenAI Agents SDK, CrewAI, AutoGen, or similar — applied in product feature delivery, not research
• Strong understanding of agentic design patterns: planning loops, tool registries, context window management, agent state machines, and failure handling
• Experience building and integrating RAG pipelines into product workflows
• Experience building production guardrails and evaluation frameworks for agentic features
• Strong full-stack engineering skills with production experience in Python and/or TypeScript
• 5+ years of full-stack software engineering with a strong shipping record
• 1+ years of hands-on experience building agentic AI features in production products
Preferred
• Experience integrating agentic capabilities into SaaS or fintech products at scale
• Familiarity with Intuit''''''''''''''''s developer platform or QuickBooks APIs
• Exposure to regulated or high-accuracy domains where agent reliability and auditability are non-negotiable
Employers have access to artificial intelligence language tools (“AI”) that help generate and enhance job descriptions and AI may have been used to create this description. The position description has been reviewed for accuracy and Dice believes it to correctly reflect the job opportunity.
- Dice Id: 91173859
- Position Id: 9065915
- Posted 18 hours ago
Company Info
About EL-Shaddai Technologies Inc
To empower businesses by providing innovative, efficient, and reliable IT talent solutions that drive growth, foster innovation, and create lasting value. We serve as the critical bridge between exceptional technology professionals and the organizations that need them.
We supply our talent network by building a deep understanding of both our clients' technical requirements and our candidates' career aspirations — ensuring a win-win for all parties.
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