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Forward-deployed AI Engineer
Career Insights for Natural Language Processing Engineer
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Based on California data
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What they do
A Natural Language Processing Engineer specializes in developing and implementing algorithms and models tailored for understanding, processing, and generating natural language text. They utilize methodologies such as tokenization, parsing, named entity recognition, part-of-speech tagging, and other NLP techniques to perform tasks including text classification, chatbot development, and other applications where the primary input or output is natural language text.
$158,568 / year median in California
Job Description
- 3.7 Long Beach, CA Job Details Full-time $125,400
- $215,975 a year 2 hours ago Benefits Wellness program Paid holidays Tuition reimbursement Paid time off 401(k) matching Qualifications RESTful API Team leadership Generative models Prompt engineering Machine intelligence Stakeholder relationship building Generative AI Full Job Description Founded in 1977 as the Senior Care Action Network, SCAN began with a simple but radical idea: that older adults deserve to stay healthy and independent.
The Job:
We're looking for engineers who enjoy solving messy healthcare problems more than building features. As a Forward Deployed AI Engineer, you'll embed with SCAN's teams to understand how work actually happens, identify opportunities where AI can make a measurable difference, and rapidly design, build, and deploy solutions that improve outcomes. Instead of working on a single product, you'll own transformation of teams and domains. One engagement might focus on reducing turnaround time for member questions, while another might improve case manager productivity. The next could automate administrative operations or help employees make better decisions with enterprise knowledge. You'll partner closely with business leaders, product owners, architects, and platform engineers to turn ambiguity into production systems.Essential Job Functions:
Business Partnership & Discovery Embed with SCAN's teams to understand workflows, operational challenges, and strategic priorities. Lead discovery activities including stakeholder interviews, workflow observation, process analysis, and opportunity assessment. Translate ambiguous business problems into clear technical requirements and measurable success criteria. Build trusted relationships with SCAN leaders and serve as a strategic technology partner. AI Solution Design & Delivery Design, develop, test, deploy, and support AI-enabled applications using SCAN's large language models (LLMs), AI agents, retrieval-augmented generation (RAG), workflow automation, APIs, and modern software engineering practices. Rapidly prototype solutions, validate concepts with users, and iterate based on business feedback. Build production-ready software using SCAN's enterprise AI platform, identifying opportunities to reverse-integrate any new capabilities to the core platform. Evaluate emerging AI technologies and recommend appropriate approaches based on business needs. Technical Leadership Translate complex business problems into scalable, maintainable technical architectures. Collaborate with architects, product managers, platform engineers, data engineers, and security teams to deliver enterprise AI solutions. Develop reusable components, patterns, and technical assets that accelerate future AI development. Contribute to engineering standards, best practices, and continuous improvement across the AI organization. Business Outcomes & Continuous Improvement Establish measurable success metrics for AI solutions and monitor business impact after deployment. Continuously optimize solutions based on operational data, user feedback, and changing business needs. Identify additional automation and AI opportunities through ongoing engagement with business partners. Support organizational adoption of AI through education, coaching, and change management. Responsible AI, Security & Governance Apply responsible AI practices, including transparency, traceability, explainability, fairness, privacy, and human oversight. Partner with security, compliance, legal, and governance teams to support safe and appropriate AI use. Document solution design, risks, controls, assumptions, and operational considerations for AI systems. Ensure AI solutions comply with organizational standards, regulatory requirements, and security policies.Your Qualifications:
Bachelor's Degree or equivalent experience in Computer science, Engineering, or a related field Deep applied understanding of LLM-based architectures, retrieval-augmented generation (RAG),vector embeddings, prompt engineering, and agent orchestration Experience designing, building, and deploying AI-enabled applications, services, workflows, and integrations. Proficiency with Azure AI Services, Azure AI Foundry, and enterprise content management platforms (SharePoint, Microsoft 365, Teams, Confluence). Strong Python (or equivalent), REST APIs, ML/LLMOps tooling, and frameworks (FastAPI, LangChain, Microsoft Agent Framework, etc.). Ability to connect business requirements to technical solutions, develop reusable components, and improve solution adoption and operational impact. Collaborative communicator, comfortable engaging non-technical stakeholders and cross-functional teams. Demonstrates curiosity, initiative, and continuous learning; adapts quickly to new frameworks and technologies. Strong business partnering skills, self-direction, and influence; able to define roadmaps, persuade skeptics, and drive adoption of new processes or technologies Demonstrates curiosity, initiative, and continuous learning; adapts quickly to new frameworks and technologies. Leadership- Skilled to develops others Business Insight
- In-Depth understanding of the business Problem Solving
- Good problem-solving skills Strategic Mindset
- Creates strategies to sustain competitive advantage