Applied AI Engineer at Hibu

King of Prussia, Pennsylvania, United States -

Full Time

Start Date

Immediate

Expiry Date

21 Aug, 26

Salary

0.0

Posted On

23 May, 26

Experience

5 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Python, TypeScript, Generative AI, Agentic AI, AWS Bedrock, Model Context Protocol, RAG Pipelines, Prompt Engineering, LangChain, LangGraph, Salesforce Integration, API Orchestration, LLM Application Development, Proof of Concept Prototyping, Software Engineering, AI Governance

Industry

Marketing Services

Description

The Applied AI Engineer is a hands-on technical role responsible for rapidly prototyping and validating GenAI, Agentic AI, and ML-powered solutions across Hibu’s business units. Based in the central AI/Enterprise Architecture team and deployed on rotational engagements with Sales & Marketing, Operations, and Product teams, this role translates business problems into working AI proof-of-concepts within weeks, not months. The Applied AI Engineer works primarily at the AI platform integration layer—orchestrating foundation models via AWS Bedrock, building agentic workflows with MCP (Model Context Protocol), designing prompt systems, and wiring AI capabilities into enterprise platforms such as Salesforce. Once a POC is validated, this role pairs with the receiving engineering team to transition the solution into production. The position requires equal comfort writing production-quality code, facilitating business stakeholder workshops, and navigating ambiguity in rapidly evolving AI technology landscapes. Primary Responsibilities: Partners with business and engineering teams to identify high-value AI use cases and translate them into scoped proof-of-concept projects Rapidly builds and iterates on GenAI and Agentic AI prototypes—targeting POC delivery in 2–4 weeks—using foundation models, prompt engineering, and agentic orchestration patterns Designs and implements agentic AI workflows leveraging Model Context Protocol (MCP) for enterprise integrations with Salesforce, marketing automation systems, customer data platforms, and internal tools Builds on Hibu’s AI platform stack including AWS Bedrock, Claude/GPT model orchestration, prompt system design, RAG pipelines, and API-first integration patterns Pairs with receiving engineering teams (2–3 sprints) to transition validated POCs into production, including architecture documentation, pair-coding sessions, and knowledge transfer Evaluates emerging AI technologies, frameworks, and tools (e.g., AWS Strands Agents, LangGraph, CrewAI) and recommends adoption based on feasibility, cost, and alignment with Hibu’s platform strategy Creates concise POC documentation including solution architecture, prompt designs, integration patterns, success criteria, and transition plans for engineering handoff Presents POC results, demos, and recommendations to both technical and business audiences, translating AI capabilities into business value language Contributes learnings, reusable components, and best practices to Hibu’s AI & Automation Hub and internal knowledge base Adheres to AI governance guidelines, responsible AI practices, data privacy protocols, and security standards (OWASP LLM Top 10, NIST AI RMF) during all prototyping and integration work Stays current with AI/ML trends through continuous learning, experimentation, and active engagement with foundation model releases, agentic AI developments, and enterprise AI integration patterns Competencies & Critical Skills: Production-level proficiency in Python and/or TypeScript with ability to rapidly prototype and ship working AI applications Hands-on experience building LLM applications: prompt engineering at system level, RAG pipelines, agentic workflows (LangChain, LangGraph, or equivalent frameworks) Strong working knowledge of foundation models (Claude, GPT, Gemini) and their enterprise integration patterns Experience with cloud AI platforms (AWS Bedrock preferred; Azure AI or Google Vertex AI acceptable) and API orchestration Understanding of Model Context Protocol (MCP) or similar AI-system integration patterns (tool use, function calling, agent-to-service communication) Strong communication skills with ability to run business stakeholder discovery sessions, present POC demos, and explain AI tradeoffs without jargon Comfort with ambiguity—can walk into a new business team, listen to unstructured problems, and define a scoped POC independently Strong handoff discipline—documents architecture decisions, writes transition guides, and pairs effectively with receiving engineering teams Innovative mindset with ability to experiment quickly, fail fast, and iterate toward effective AI-native solutions Experience and Qualifications: Required/ Preferred: Bachelor’s Degree in Computer Science, Software Engineering, AI/ML, or related field Required 5–8 years of software engineering experience with at least 2 years focused on AI/ML application development Required Hands-on experience building LLM-powered applications (RAG, prompt engineering, agentic workflows) shipped to real users or business stakeholders Required Production-level proficiency in Python and/or TypeScript for rapid prototyping and application development Required Experience with cloud AI platforms (AWS Bedrock preferred; SageMaker, Azure AI, or Vertex AI acceptable) Required Strong API integration skills (REST, webhooks, MCP or similar agent-to-service patterns) Required Experience with agentic AI frameworks/platforms (LangChain, LangGraph, CrewAI, AWS Strands Agents, Claude Managed Agents, AWS Agentcore or equivalent) Required Salesforce ecosystem familiarity and CRM integration experience Preferred Familiarity with AI evaluation frameworks, prompt testing, and LLM output quality assurance Preferred Experience in digital marketing technology, SMB SaaS platforms, or sales/marketing operations Preferred Demonstrated ability to facilitate business discovery sessions and present POC demos to non-technical stakeholders Required Experience pairing with engineering teams to transition prototypes into production systems Required Experience with AI-DLC Preferred Agile Scrum Required #LI-CK1 #LI-HYBRID Working with us means joining a team of truly extraordinary people working to improve communities across the country. Joining our team means not only working in a fun environment with smart people, but also being able to take advantage of our competitive compensation, ongoing training, incentives, and generous benefits package. Learn more about the Hibu culture here: Culture at Hibu NOTE: Hibu is an Equal Opportunity Employer, and consistent with applicable law, provides reasonable accommodations for qualified individuals with disabilities and disabled veterans in completing our job application process. If you need reasonable accommodation and/or are having difficulty completing our online application process due to a disability you may use the following email address applicationaccomodation@hibu.com : Please include your name and contact information and the title of the position you are interested in. Note: this is not for general employment inquires or correspondence. Hibu will only respond to requests related to those who need assistance with the online application process due to a disability

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Responsibilities

Rapidly prototype and validate GenAI and Agentic AI solutions to solve business problems across various units. Orchestrate foundation models and integrate AI capabilities into enterprise platforms before transitioning them to production engineering teams.