AI Solutions Expert

We need to output HTML fragment with sections: About the role, Responsibilities, Requirements (or Qualifications), Skills maybe, Benefits, Pay, Schedule. Must include only sections with real specific content. No placeholder like "commensurate with experience". We have content: About the role: description of role. Responsibilities: list of duties. Requirements/Qualifications: list of qualifications (minimum and preferred). Skills: maybe combine? But we can have a Skills section if there is explicit skill list. The posting includes many skill items under qualifications. Could treat them as Requirements. Benefits: they list salary and benefits: competitive salary and generous benefits package, including at no cost: full health and dental for you and your dependents, retirement and HSA accounts, short- and long-term disability insurance, life and accident insurance, paid time off, and 11 federal holidays. So we have Benefits section. Pay: they mention competitive salary but not specific number. That's vague; we should not create Pay section unless posting actually states them. It says "competitive salary" but no number; that's vague. According to rule: never emit a heading followed by filler/placeholder text (e.g., "commensurate with experience", "not specified", "N/A", "varies", "TBD") and never create Pay/Schedule/Benefits sections unless the posting actually states them. "competitive salary" is vague but still states something? It's not a specific number; but it's still a statement about pay. However rule says avoid filler/placeholder like "commensurate with experience". "competitive salary" might be considered vague but not placeholder? It's still non-specific. Safer to omit Pay section. Schedule: they mention location hybrid with remote work options as approved by the COR. That's schedule info. Could create Schedule section with that detail. It's specific: Hybrid (with remote work options as approved by the COR). That's not placeholder. So include Schedule. We must not repeat job title as heading. No Job ID. Remove boilerplate: EEO, equal-opportunity, scam-warning, application instructions, etc. Also remove "Applicants selected will be subject to a pre-employment background and reference check." That's maybe boilerplate but it's a requirement? It's about background check; could be included under Requirements? Might be considered boilerplate but it's a condition. The instruction: Remove cookie/navigation/legal/EEO/equal-opportunity/scam-warning boilerplate, duplicated lines, and application instructions. Background check might be legal but not EEO. Might keep? It's a condition of employment. Could be included under Requirements as a note. But maybe safer to keep as part of Requirements? However it's not a skill. Could be a separate line under Requirements. I'd include it as a bullet under Requirements. We need to use

for section headings. Use

• for any list of duties/requirements/benefits, and

  for prose. We need to preserve ALL substantive information; do not invent or summarize away detail. Let's extract sections: About the role: paragraph describing role: "Lexical Intelligence provides software and services related to processing large-scale biomedical information sources. Our NLP and analytics software is used by policy and decision makers to evaluate and prioritize current and emerging areas of research. We are looking for an Artificial Intelligence (AI) Solutions Engineer with analytical experience to work for a federal client in Bethesda, MD. The AI Solutions Engineer will design, develop, and operationalize AI-driven capabilities that enable advanced automation and decision support across a range of applications. This role focuses on piloting and implementing AI solutions, including standing up lightweight applications and applets within a shared infrastructure environment, integrating foundation models, and translating emerging AI techniques into practical tools. The engineer will work across the full lifecycle of AI systems, supporting data preparation, model integration, evaluation, deployment, and monitoring, while collaborating with cross-functional teams to ensure solutions are scalable, reliable, and aligned with mission needs." That's prose. Responsibilities: The posting includes "Responsibilities include ensuring compliance with organizational security and privacy policies, protecting sensitive data and systems, reporting security incidents, and participating in required cybersecurity training. The role may also involve implementing best practices related to access control, data handling, and risk mitigation within the scope of assigned duties." Also earlier responsibilities: design, develop, operationalize AI-driven capabilities, piloting and implementing AI solutions, standing up lightweight applications and applets, integrating foundation models, translating emerging AI techniques into practical tools, work across full lifecycle supporting data preparation, model integration, evaluation, deployment, monitoring, collaborating with cross-functional teams. Those are more like duties. We'll combine into a list. Requirements/Qualifications: Minimum qualifications list: Eight to 10 years of relevant experience with items below: Strong programming and AI/ML development skills, including Python, experience with modern frameworks, and with integrating AI models into existing software architectures; Experience designing and deploying AI solutions end-to-end, including integrating models into applications or shared infrastructure; Strong background in algorithm design and data structures; comfort with software testing, debugging, and system architecture; Solid data analysis and data engineering capability, including working with large datasets and translating findings into usable outputs; Proficiency with cloud-based and containerized environments (e.g., AWS, Kubernetes) to support scalable AI workloads; Ability to evaluate, iterate, and operationalize AI solutions, including performance measurement, experimentation, and collaboration with cross-functional teams; Bachelor’s degree in Computer Science, Software Engineering, Data Science or related quantitative area; Ability to obtain a Public Trust Clearance. Preferred qualifications list: Ph.D. or advanced Master's degree in a relevant scientific or quantitative discipline; Experience supporting NIH or other federal biomedical research organizations; Experience applying large language models (LLMs) to scientific analysis, information extraction, summarization, or question answering; Experience with Retrieval-Augmented Generation (RAG), embeddings, vector databases, and semantic search; Experience evaluating AI systems using benchmark-driven and human-in-the-loop methodologies; Experience analyzing publications, grants, patents, clinical trials, or other large-scale scientific datasets; Familiarity with MLOps practices such as model versioning, monitoring, and lifecycle management in production environments; Experience building AI prototypes or pilot applications in shared or enterprise environments; Knowledge of data governance, security, and compliance considerations, particularly in regulated or federal environments; Exposure to modern data platforms and distributed processing frameworks (e.g., Spark, Databricks); Strong communication skills with the ability to explain AI concepts and analytical findings to non-technical stakeholders; Experience working in cross-functional or product-oriented teams to translate requirements into technical solutions. Desired characteristics: Strong scientific reasoning and critical thinking; Ability to interpret complex scientific literature; Curiosity for emerging AI technologies and biomedical research; Commitment to reproducible, transparent, and high-quality analytical methods. We could combine all into Requirements section, maybe split into Minimum and Preferred subheadings? But only allowed headings are the listed ones; we could still use

  for Requirements and then within that we could have

  or

  . The instruction: Use

  for section headings (e.g. About the role, Responsibilities, Requirements, Qualifications, Skills, Benefits, Pay, Schedule). So we can have either Requirements or Qualifications. We'll pick Requirements. Could also have Skills separate but we can incorporate skill items into Requirements. We need to avoid duplication. Ensure we preserve all substantive info. Benefits: list as

  • . Schedule: mention location hybrid with remote work options as approved by the COR. We must not include boilerplate like EEO, equal opportunity, etc. Also remove "All candidates will be required to undergo a background check and must be authorized to work in the United States." That's maybe legal but not EEO; could be considered a requirement. It's a condition. I'd include it under Requirements as a bullet. Also remove "Applicants selected will be subject to a pre-employment background and reference check." That's similar. We'll keep background check requirement. Now construct HTML. Structure:

    About the role

    ...

    Responsibilities

    • Design, develop, and operationalize AI-driven capabilities that enable advanced automation and decision support across a range of applications.
    • Pilot and implement AI solutions, including standing up lightweight applications and applets within a shared infrastructure environment, integrating foundation models, and translating emerging AI techniques into practical tools.
    • Work across the full lifecycle of AI systems, supporting data preparation, model integration, evaluation, deployment, and monitoring.
    • Collaborate with cross-functional teams to ensure solutions are scalable, reliable, and aligned with mission needs.
    • Ensure compliance with organizational security and privacy policies, protect sensitive data and systems, report security incidents, and participate in required cybersecurity training.
    • Implement best practices related to access control, data handling, and risk mitigation within the scope of assigned duties.

    Requirements

    • Eight to 10 years of relevant experience.
    • Strong programming and AI/ML development skills, including Python, experience with modern frameworks, and integrating AI models into existing software architectures.
    • Experience designing and deploying AI solutions end-to-end, including integrating models into applications or shared infrastructure.
    • Strong background in algorithm design and data structures; comfort with software testing, debugging, and system architecture.
    • Solid data analysis and data engineering capability, including working with large datasets and translating findings into usable outputs.
    • Proficiency with cloud-based and containerized environments (e.g., AWS, Kubernetes) to support scalable AI workloads.
    • Ability to evaluate, iterate, and operationalize AI solutions, including performance measurement, experimentation, and collaboration with cross-functional teams.
    • Bachelor’s degree in Computer Science, Software Engineering, Data Science or related quantitative area.
    • Ability to obtain a Public Trust Clearance.
    • Must be authorized to work in the United States and undergo a background check.
    • Preferred: Ph.D. or advanced Master's degree in a relevant scientific or quantitative discipline.
    • Preferred: Experience supporting NIH or other federal biomedical research organizations.
    • Preferred: Experience applying large language models (LLMs) to scientific analysis, information extraction, summarization, or question answering.
    • Preferred: Experience with Retrieval-Augmented Generation (RAG), embeddings, vector databases, and semantic search.
    • Preferred: Experience evaluating AI systems using benchmark-driven and human-in-the-loop methodologies.
    • Preferred: Experience analyzing publications, grants, patents, clinical trials, or other large-scale scientific datasets.
    • Preferred: Familiarity with MLOps practices such as model versioning, monitoring, and lifecycle management in production environments.
    • Preferred: Experience building AI prototypes or pilot applications in shared or enterprise environments.
    • Preferred: Knowledge of data governance, security, and compliance considerations, particularly in regulated or federal environments.
    • Preferred: Exposure to modern data platforms and distributed processing frameworks (e.g., Spark, Databricks).
    • Preferred: Strong communication skills with the ability to explain AI concepts and analytical findings to non-technical stakeholders.
    • Preferred: Experience working in cross-functional or product-oriented teams to translate requirements into technical solutions.
    • Desired: Strong scientific reasoning and critical thinking.
    • Desired: Ability to interpret complex scientific literature.
    • Desired: Curiosity for emerging AI technologies and biomedical research.
    • Desired: Commitment to reproducible, transparent, and high-quality analytical methods.

    Benefits

    • Competitive salary (not specified)
    • Full health and dental coverage for employee and dependents at no cost.
    • Retirement and HSA accounts.
    • Short- and long-term disability insurance.
    • Life and accident insurance.
    • Paid time off.
    • 11 federal holidays.
    But we said we should not create Pay section unless posting actually states them. Benefits we can include