Federal Solution Leader
for section headings (e.g. About the role, Responsibilities, Requirements, Qualifications, Skills, Benefits, Pay, Schedule). We should include sections only when posting has real specific content. We have description (intro) that could be "About the role". Then Responsibilities (list). Then Qualifications (list). Then Preferred Qualifications (maybe as "Preferred Qualifications" but not in list of headings? It's similar to Qualifications; we could treat as part of Qualifications or separate "Preferred Qualifications". The allowed headings list includes Qualifications, Skills, Benefits, Pay, Schedule. Not Preferred Qualifications. But we could still include a heading if content exists? The instruction says use those examples but not limited? It says "Use for section headings (e.g. About the role, Responsibilities, Requirements, Qualifications, Skills, Benefits, Pay, Schedule)." It suggests those are examples; we can use others if needed but better to stick to those. Preferred Qualifications could be under Qualifications as a subsection? But we need to preserve all substantive info. Could combine Qualifications and Preferred Qualifications into one Qualifications section with two sublists? Might be okay. However we need to avoid filler. We have Pay: "Virginia Base Pay Range $130,000—$167,000 USD". That's specific pay info, so we should include a Pay section. Benefits: "C3 AI provides excellent benefits, a competitive compensation package and generous equity plan." That's benefits info, so include Benefits section. Schedule: not mentioned, so omit. Requirements: not separate; qualifications cover. Skills: maybe not separate; we could include Skills if we want but not needed. We'll include About the role, Responsibilities, Qualifications, Benefits, Pay.
We need to use - for any list of duties/requirements/benefits. For Benefits we have a sentence; could be a
but also could be list? It's not a list. Use
for prose. For Responsibilities we have many items each starting with a bold heading? Actually responsibilities list includes items like "Technical architecture.", "Stay hands-on.", etc. Each is a sentence with a bold label then description. We'll treat each as
- . For Qualifications we have bullet-like paragraphs; we can make
- for each qualification requirement. Preferred qualifications we could also include as
- under Qualifications maybe separate list labeled "Preferred". But we can just add them as additional
- under Qualifications with maybe a note? Might be okay.
We must not repeat job title as heading. No Job ID. Remove boilerplate like EEO etc. Also remove "Learn more at:" etc. Also remove "C3 AI (NYSE: AI), is the Enterprise AI application software company." That's intro but could be part of About the role? It's generic company description; maybe we keep as part of About the role? It's substantive but maybe not role-specific. However we need to preserve ALL substantive information; we can include it in About the role paragraph.
We must not include duplicated lines. Also remove application instructions (none). Remove EEO/equal-opportunity/scams. At end there is EEO statement; remove.
Now craft HTML:
About the role
C3 AI (NYSE: AI), is the Enterprise AI application software company. C3 AI delivers a family of fully integrated products including the C3 Agentic AI Platform, an end-to-end platform for developing, deploying, and operating enterprise AI applications, C3 AI applications, a portfolio of industry-specific SaaS enterprise AI applications that enable the digital transformation of organizations globally, and C3 Generative AI, a suite of domain-specific generative AI offerings for the enterprise. Learn more at: C3 AI Federal Solution Leaders are senior technical experts who bring deep mission knowledge and hands-on engineering to the cross-functional teams delivering enterprise AI for Federal, Defense, and Intelligence Community customers. It is a hands-on, deeply technical role that also demands real mission fluency: you will contribute solution and data architecture, the ability to build and prototype directly, deep mission-domain expertise, and executive stakeholder communication—embedding with government customers to help take our products from “design” to “in production” in secure and often classified environments. We hire for this blend from two directions: strong engineers who have gone deep on the mission, and mission experts who are genuinely technical. Working one account at a time as part of a delivery team, you will help scope the mission workflow with government and technical stakeholders, quantify the highest-value AI/ML opportunities, shape the architecture, get hands-on to close the gaps, and drive toward measurable mission impact. You will work alongside Forward Deployed Engineers and data scientists who build much of the production solution, bringing the mission expertise and technical judgment to reason from first principles, inspect the data yourself, and determine whether an AI-driven recommendation is technically and operationally credible. Federal Solution Leaders work on highly visible, mission-critical AI initiatives, for example: Applying AI-driven supply chain solutions to transform military supply chains—reducing lead times, decreasing inventory holding costs, and improving warfighter readiness.Applying generative AI to transform intelligence analysis, enabling analysts to rapidly access and synthesize critical information.Applying predictive-maintenance ML to anticipate critical failures on military equipment and improve equipment readiness.Leveraging AI to optimize enterprise planning and programmatic workflows in support of key mission initiatives, organizational productivity, and decision-making.
But note we have duplicated "Learn more at: C3 AI Federal Solution Leaders..." Actually the text includes "Learn more at: C3 AI Federal Solution Leaders are senior technical experts..." That seems like a formatting error; we should keep the sentence as is? Might be weird. Perhaps we should remove "Learn more at:" as it's likely a placeholder. The instruction: remove duplicated lines, boilerplate. "Learn more at:" could be considered navigation? Not sure. Safer to keep it? It's not boilerplate; it's part of the description but seems odd. I'd keep it as part of the paragraph.
Now Responsibilities:
Responsibilities
- Technical architecture. Help shape data flow, integration topology, identity model, and deployment architecture across the customer’s environment, including on-premises, air-gapped, and government cloud infrastructure.
- Stay hands-on. Prototype, build, and debug alongside your team when the problem calls for it—reading and writing code, wiring up data pipelines and integrations, and using modern and agentic coding tools. You set technical direction; you don’t stay above the details.
- Opportunity identification and value. Develop a deep understanding of the mission and quantify the highest-impact AI/ML opportunities, translating complex mission and operational challenges into tractable AI, machine learning, optimization, and software problems with clearly defined requirements, success criteria, and expected mission value.
- Technical direction. Help shape the solution’s technical roadmap and inform what’s in scope, what’s a one-off, and what should become product.
- Technical leadership within the team. Work as part of a cross-functional team of Forward Deployed Engineers, data scientists, product managers, and industry experts, providing technical and mission leadership that helps set priorities and keep the team aligned around customer outcomes.
- Manage technical risk. Stay on top of the technical risks and dependencies in your part of the solution. When something slips, know first and flag first.
- Stakeholder communication. Run customer working sessions, brief government executive sponsors and mission owners, and write clean status updates that senior stakeholders will actually read.
- Ship into production. Deploy from dev through UAT into production—including integration with customer data stores, mission systems, ERP/CRM systems, and cloud environments (AWS, Azure, GCP, and their government regions).
- Enterprise and federal readiness. Ensure the platform is configured, secured, monitored, and accredited to meet federal security and compliance requirements (e.g., FedRAMP, DoD Impact Levels IL4–IL6, NIST 800-53/800-171, and applicable ATO processes).
- Bridge field back to product. Push field learnings into the core platform so the next mission deployment is faster and more repeatable.
- Account growth. Partner with Sales to identify expansion opportunities within the account—surfacing new mission use cases, supporting renewal conversations, and converting successful deployments into long-term customer relationships.
Qualifications: include required qualifications and preferred qualifications maybe as separate lists under same heading? Could do two with headings? But we cannot add extra headings besides allowed ones. Could embed a saying "Preferred qualifications:" then list. That's okay.
Thus:
Qualifications
- U.S. citizenship required.
- Active U.S. Government Top Secret/SCI security clearance required; CI or Full-Scope Polygraph strongly preferred.
- Technical credibility (required). Able to architect enterprise AI and data solutions, get hands-on to prototype and build (e.g., Python, SQL, or similar), inspect and reason about data directly, and hold your own with engineers and data scientists.
- Depth from one of two directions (required). Either (a) a strong software or data engineering background, with years building and shipping production systems; or (b) deep military, intelligence, or federal mission expertise paired with demonstrated technical fluency—building tools, scripting and analysis, data-heavy programs, or leading technical teams.
- Bachelor’s degree required in Computer Science, Software Engineering, Engineering, or a related technical or quantitative discipline; advanced degree a plus.
- Demonstrated track record of building and delivering solutions or systems from concept through production, with the judgment to reason from first principles and troubleshoot when things break.
- Deep subject-matter expertise in at least one federal mission domain (e.g., defense, intelligence, aerospace, logistics/supply chain, or another mission area) sufficient to challenge assumptions and earn credibility with government stakeholders.
- Experience working directly with senior technical and executive stakeholders—comfortable in both mission/executive conversations and deep technical design sessions.
- Familiarity with enterprise data environments (cloud data warehouses such as Snowflake, Databricks, BigQuery, or Redshift; REST/GraphQL APIs; common ERP or CRM platforms) and modern deployment practices (CI/CD, containerization, cloud-native services, infrastructure-as-code)—or the ability to ramp quickly.
Preferred qualifications:
- Prior experience delivering to the U.S. Federal government, especially the Department of War (DoW/DoD), the Intelligence Community, or Aerospace & Defense customers.
- CI or Full-Scope Polygraph, and prior experience delivering software in classified, SCIF, or air-gapped environments.
- Prior U.S. military or government service, or experience as a technical lead embedded within a defense or Intelligence Community program.
- Experience deploying AI/ML platforms or data-heavy enterprise applications at scale, including generative AI, predictive maintenance, optimization, or decision-support solutions.
- Experience with government cloud environments (AWS GovCloud, Azure Government) and managed ML/AI services, and with accreditation processes (FedRAMP, DoD IL, ATO).
- Prior experience as a tech lead or staff engineer at a SaaS or enterprise software vendor with a forward-deployed or professional-services motion.
- Awareness of export-control and handling requirements (e.g., ITAR/EAR) relevant to defense and intelligence work.
- Proven ability to turn an ambiguous, loosely scoped mission problem into a clean, repeatable deployment pattern.
- Candidates must be authorized to work in the United States without the need
- for any list of duties/requirements/benefits. For Benefits we have a sentence; could be a
but also could be list? It's not a list. Use
for prose. For Responsibilities we have many items each starting with a bold heading? Actually responsibilities list includes items like "Technical architecture.", "Stay hands-on.", etc. Each is a sentence with a bold label then description. We'll treat each as
- . For Qualifications we have bullet-like paragraphs; we can make
- for each qualification requirement. Preferred qualifications we could also include as
- under Qualifications maybe separate list labeled "Preferred". But we can just add them as additional
- under Qualifications with maybe a note? Might be okay.
We must not repeat job title as heading. No Job ID. Remove boilerplate like EEO etc. Also remove "Learn more at:" etc. Also remove "C3 AI (NYSE: AI), is the Enterprise AI application software company." That's intro but could be part of About the role? It's generic company description; maybe we keep as part of About the role? It's substantive but maybe not role-specific. However we need to preserve ALL substantive information; we can include it in About the role paragraph.
We must not include duplicated lines. Also remove application instructions (none). Remove EEO/equal-opportunity/scams. At end there is EEO statement; remove.
Now craft HTML:
About the role
C3 AI (NYSE: AI), is the Enterprise AI application software company. C3 AI delivers a family of fully integrated products including the C3 Agentic AI Platform, an end-to-end platform for developing, deploying, and operating enterprise AI applications, C3 AI applications, a portfolio of industry-specific SaaS enterprise AI applications that enable the digital transformation of organizations globally, and C3 Generative AI, a suite of domain-specific generative AI offerings for the enterprise. Learn more at: C3 AI Federal Solution Leaders are senior technical experts who bring deep mission knowledge and hands-on engineering to the cross-functional teams delivering enterprise AI for Federal, Defense, and Intelligence Community customers. It is a hands-on, deeply technical role that also demands real mission fluency: you will contribute solution and data architecture, the ability to build and prototype directly, deep mission-domain expertise, and executive stakeholder communication—embedding with government customers to help take our products from “design” to “in production” in secure and often classified environments. We hire for this blend from two directions: strong engineers who have gone deep on the mission, and mission experts who are genuinely technical. Working one account at a time as part of a delivery team, you will help scope the mission workflow with government and technical stakeholders, quantify the highest-value AI/ML opportunities, shape the architecture, get hands-on to close the gaps, and drive toward measurable mission impact. You will work alongside Forward Deployed Engineers and data scientists who build much of the production solution, bringing the mission expertise and technical judgment to reason from first principles, inspect the data yourself, and determine whether an AI-driven recommendation is technically and operationally credible. Federal Solution Leaders work on highly visible, mission-critical AI initiatives, for example: Applying AI-driven supply chain solutions to transform military supply chains—reducing lead times, decreasing inventory holding costs, and improving warfighter readiness.Applying generative AI to transform intelligence analysis, enabling analysts to rapidly access and synthesize critical information.Applying predictive-maintenance ML to anticipate critical failures on military equipment and improve equipment readiness.Leveraging AI to optimize enterprise planning and programmatic workflows in support of key mission initiatives, organizational productivity, and decision-making.
But note we have duplicated "Learn more at: C3 AI Federal Solution Leaders..." Actually the text includes "Learn more at: C3 AI Federal Solution Leaders are senior technical experts..." That seems like a formatting error; we should keep the sentence as is? Might be weird. Perhaps we should remove "Learn more at:" as it's likely a placeholder. The instruction: remove duplicated lines, boilerplate. "Learn more at:" could be considered navigation? Not sure. Safer to keep it? It's not boilerplate; it's part of the description but seems odd. I'd keep it as part of the paragraph. Now Responsibilities:Responsibilities
- Technical architecture. Help shape data flow, integration topology, identity model, and deployment architecture across the customer’s environment, including on-premises, air-gapped, and government cloud infrastructure.
- Stay hands-on. Prototype, build, and debug alongside your team when the problem calls for it—reading and writing code, wiring up data pipelines and integrations, and using modern and agentic coding tools. You set technical direction; you don’t stay above the details.
- Opportunity identification and value. Develop a deep understanding of the mission and quantify the highest-impact AI/ML opportunities, translating complex mission and operational challenges into tractable AI, machine learning, optimization, and software problems with clearly defined requirements, success criteria, and expected mission value.
- Technical direction. Help shape the solution’s technical roadmap and inform what’s in scope, what’s a one-off, and what should become product.
- Technical leadership within the team. Work as part of a cross-functional team of Forward Deployed Engineers, data scientists, product managers, and industry experts, providing technical and mission leadership that helps set priorities and keep the team aligned around customer outcomes.
- Manage technical risk. Stay on top of the technical risks and dependencies in your part of the solution. When something slips, know first and flag first.
- Stakeholder communication. Run customer working sessions, brief government executive sponsors and mission owners, and write clean status updates that senior stakeholders will actually read.
- Ship into production. Deploy from dev through UAT into production—including integration with customer data stores, mission systems, ERP/CRM systems, and cloud environments (AWS, Azure, GCP, and their government regions).
- Enterprise and federal readiness. Ensure the platform is configured, secured, monitored, and accredited to meet federal security and compliance requirements (e.g., FedRAMP, DoD Impact Levels IL4–IL6, NIST 800-53/800-171, and applicable ATO processes).
- Bridge field back to product. Push field learnings into the core platform so the next mission deployment is faster and more repeatable.
- Account growth. Partner with Sales to identify expansion opportunities within the account—surfacing new mission use cases, supporting renewal conversations, and converting successful deployments into long-term customer relationships.
- with headings? But we cannot add extra headings besides allowed ones. Could embed a
- U.S. citizenship required.
- Active U.S. Government Top Secret/SCI security clearance required; CI or Full-Scope Polygraph strongly preferred.
- Technical credibility (required). Able to architect enterprise AI and data solutions, get hands-on to prototype and build (e.g., Python, SQL, or similar), inspect and reason about data directly, and hold your own with engineers and data scientists.
- Depth from one of two directions (required). Either (a) a strong software or data engineering background, with years building and shipping production systems; or (b) deep military, intelligence, or federal mission expertise paired with demonstrated technical fluency—building tools, scripting and analysis, data-heavy programs, or leading technical teams.
- Bachelor’s degree required in Computer Science, Software Engineering, Engineering, or a related technical or quantitative discipline; advanced degree a plus.
- Demonstrated track record of building and delivering solutions or systems from concept through production, with the judgment to reason from first principles and troubleshoot when things break.
- Deep subject-matter expertise in at least one federal mission domain (e.g., defense, intelligence, aerospace, logistics/supply chain, or another mission area) sufficient to challenge assumptions and earn credibility with government stakeholders.
- Experience working directly with senior technical and executive stakeholders—comfortable in both mission/executive conversations and deep technical design sessions.
- Familiarity with enterprise data environments (cloud data warehouses such as Snowflake, Databricks, BigQuery, or Redshift; REST/GraphQL APIs; common ERP or CRM platforms) and modern deployment practices (CI/CD, containerization, cloud-native services, infrastructure-as-code)—or the ability to ramp quickly.
- Prior experience delivering to the U.S. Federal government, especially the Department of War (DoW/DoD), the Intelligence Community, or Aerospace & Defense customers.
- CI or Full-Scope Polygraph, and prior experience delivering software in classified, SCIF, or air-gapped environments.
- Prior U.S. military or government service, or experience as a technical lead embedded within a defense or Intelligence Community program.
- Experience deploying AI/ML platforms or data-heavy enterprise applications at scale, including generative AI, predictive maintenance, optimization, or decision-support solutions.
- Experience with government cloud environments (AWS GovCloud, Azure Government) and managed ML/AI services, and with accreditation processes (FedRAMP, DoD IL, ATO).
- Prior experience as a tech lead or staff engineer at a SaaS or enterprise software vendor with a forward-deployed or professional-services motion.
- Awareness of export-control and handling requirements (e.g., ITAR/EAR) relevant to defense and intelligence work.
- Proven ability to turn an ambiguous, loosely scoped mission problem into a clean, repeatable deployment pattern.
- Candidates must be authorized to work in the United States without the need
saying "Preferred qualifications:" then list. That's okay. Thus:
Qualifications
Preferred qualifications: