Data Solutions Architect | AI
for sections like About the role, Responsibilities, Requirements, Qualifications, Skills, Benefits, Pay, Schedule. Use - for any list of duties/requirements/benefits, and
for prose. Do NOT repeat job title as heading. Do NOT put Job ID/requisition numbers as headings. Preserve all substantive info; remove boilerplate (cookie/navigation/legal/EEO/equal-opportunity/scam-warning, duplicated lines, application instructions). Include a section only when posting has real specific content for it; never emit heading with filler/placeholder text. Prefer few substantive sections over many thin ones.
We need to parse the posting: It starts with "Who is Trace3?" then description of company. Then "Street-Smart - Thriving in Dynamic Times", "Juice - The “Stuff” it takes to be a Needle Mover", "Teamwork - Humble, Hungry and Smart". Those seem like cultural values. Then "What You’ll Do As a Data Solutions Architect..." with responsibilities. Then "Required Qualifications", "Preferred Qualifications". Then "Actual salary will be based on a variety of factors..." then "Estimated Pay Range: $160,000 USD - $180,000 USD". Then "The Perks" list of benefits. Then "Our Commitment" (EEO etc) which is boilerplate to remove. Also "If you require a reasonable accommodation..." etc. Also recruitment agency note.
We need to output sections: maybe About the role (company overview), Responsibilities (What You'll Do), Requirements (maybe combine Required Qualifications?), Qualifications (maybe Preferred?), Skills (maybe list of technical skills?), Benefits (The Perks), Pay (Estimated Pay Range). Schedule not present, so omit.
We must not create sections with filler. So we need to ensure each section has substantive content.
We need to decide which headings to use: About the role, Responsibilities, Requirements, Qualifications, Skills, Benefits, Pay.
We must not repeat job title as heading. The job title is Data Solutions Architect (implied). We'll not put that as heading.
We need to use
for each section heading.
Inside sections, use
for prose,
- for lists.
We need to preserve all substantive info; do not invent or summarize away detail. So we need to include details from company overview, responsibilities, required qualifications, preferred qualifications, skills (maybe list of technical proficiencies), benefits, pay.
We must remove boilerplate: EEO statements, accommodation request, recruitment agency note, maybe also "Our Commitment" etc. Also remove duplicated lines.
We need to keep cultural values? Those are part of company overview maybe. Could include in About the role.
We need to ensure we don't include placeholder like "commensurate with experience" etc. Not present.
Now craft HTML.
Structure:
About the role
Trace3 is a leading Transformative IT Authority, providing unique technology solutions and consulting services to clients. Equipped with elite engineering and dynamic innovation, we empower IT executives and their organizations to achieve competitive advantage through a process of Integrate, Automate, Innovate. Our culture embodies the spirit of a startup with the advantage of a scalable business. Employees can grow their career and have fun while doing it! Trace3 is headquartered in Irvine, California, employs more than 1,200 people across the United States, with major field offices in Denver, Indianapolis, Grand Rapids, Lexington, Los Angeles, Louisville, Texas, San Francisco.
Maybe also include the cultural values: Street-Smart, Juice, Teamwork. Could embed as list.
Better to put them as - within About the role.
But we need to avoid duplication.
Let's include a list of cultural traits.
Responsibilities
As a Data Solutions Architect, you will own the end-to-end lifecycle of technical proof work across the Data and Experiences BU. Your work will directly support Practice Directors, field SAs, and the Delivery Organization across the Intelligent Enterprise, Consumer Experiences, and Data and Analytics practices.
Then list duties: Pre-Sales and Client-Facing Technical Work, AI Innovation and Capability Development, Delivery Enablement, Thought Leadership and Team Contribution. Each with subpoints.
We need to use - for any list of duties/requirements/benefits. So we can have a top-level
with each major duty as - , and inside each
- we can have further
for subpoints? The instruction: Use - for any list of duties/requirements/benefits. It doesn't forbid nested lists, but we can keep simple: each duty as
- and include prose inside.
We'll need to preserve all substantive detail; not summarize away. So we need to include the details from each bullet.
Let's extract responsibilities sections:
Pre-Sales and Client-Facing Technical Work:
- design, build, and present client-facing proofs of concept (POCs) and proofs of value (POVs) that demonstrate Trace3’s technical differentiation. These are not vendor-provided sandbox logins or generic demos. They are live, configured, Trace3-branded environments built on the client’s data, the client’s workflows, and the client’s integration points. You will own the scoping, architecture, build, and presentation of these assets.
- lead AI capability demonstrations across the BU’s core technology plays, including agentic AI architectures, retrieval-augmented generation (RAG) systems, multimodal AI pipelines, MLOps platforms, and AI-native data and analytics stacks.
- be the person in the room who can answer the question “can you show me that working?” with a yes – and then show it.
- partner with Practice Directors and field SAs during active sales pursuits to define POC success criteria, scope minimum viable architectures, and ensure that every proof of concept is designed to answer a specific technical question – not to impress, but to advance the deal.
AI Innovation and Capability Development:
- be a visible, opinionated AI forward thinker within the BU.
- track emerging AI capabilities across the vendor ecosystem, evaluate their relevance to Trace3’s client base, and translate that evaluation into actionable technical assets: working prototypes, architecture reference guides, and intake recommendations for the Accelerators build pipeline.
- build reusable AI accelerator assets – prompt libraries, agent frameworks, RAG pipeline templates, evaluation harnesses, and fine-tuning playbooks – that reduce the time required to stand up AI capabilities from scratch on client engagements.
- build these assets in collaboration with the TAMs, Practice Directors, and Delivery teams who will use them.
- drive the Accelerators group’s contribution to the Pre-Sales Intelligence Evaluation Suite (CXE, DPE, SPE, IFE) – a set of AI-powered research evaluations that give Trace3 sellers an informed, opinionated starting position before the first client meeting.
- build, test, and refine the agent prompts, research workflows, and output templates that make these evaluations repeatable and high-quality.
Delivery Enablement:
- build technical tooling that makes the Delivery Organization faster and more consistent. This includes configuration automation scripts that reduce platform stand-up time, automated UAT frameworks that catch issues early in the delivery lifecycle, and documentation automation pipelines that generate as-built artifacts as a byproduct of the delivery process rather than a manual effort at the end.
- serve as the technical escalation path for Practice Directors and SAs who encounter questions they cannot answer – new vendor capabilities, integration edge cases, regulatory requirements that affect architecture decisions.
- research, document, and communicate findings in a form that the requesting team can use immediately.
Thought Leadership and Team Contribution:
- contribute to the Accelerators group’s internal knowledge base, publishing technical briefs, architecture patterns, and lessons learned from every significant POC or accelerator build.
- mentor junior team members and contribute to the continuous development of the team’s collective capability.
- represent the Accelerators group in vendor technical briefings, partner advisory boards, and internal BU forums.
Now Required Qualifications list:
- Bachelor’s degree in computer science, engineering, mathematics, or a related field, or equivalent professional experience
- 5 or more years of experience in solutions architecture, data architecture, or AI architecture with a track record of client-facing technical delivery
- 3 or more years of hands-on experience building and deploying AI or machine learning solutions in production or near-production environments
- Demonstrated experience designing and building POCs and POVs for enterprise clients, including scoping, architecture, build, and executive presentation
- Proficiency in Python and at least one additional language (SQL, Scala, JavaScript, or R)
- Hands-on experience with cloud data platforms (Snowflake, Databricks, or equivalent) and at least one major cloud provider (AWS, Azure, or GCP)
- Working knowledge of modern AI architectures including large language models (LLMs), RAG systems, vector stores, knowledge graphs, and agentic frameworks
- Outstanding communication and presentation skills with both technical and executive audiences, including the ability to present complex AI concepts to non-technical stakeholders
- Strong organizational and time management skills with the ability to manage multiple concurrent POC and accelerator builds in a fast-moving environment
Preferred Qualifications list:
- Master’s degree in computer science, AI, machine learning, or a related field
- Experience with MLOps platforms and practices (model versioning, monitoring, drift detection, retraining pipelines)
- Experience with agentic AI frameworks (LangChain, LangGraph, AutoGen, CrewAI, or equivalent)
- Experience with ETL and data pipeline architecture at scale (Apache Spark, Kafka, Flink, or equivalent)
- Familiarity with CCaaS, UCaaS, or contact center AI platforms (Genesys, Five9, Cisco, or equivalent)
- Relevant AI or cloud certifications (Azure AI Engineer, Google Cloud Professional ML Engineer, AWS Machine Learning Specialty, or equivalent)
- Experience in a consulting or professional services environment where you have owned client-facing technical deliverables end-to-end
- Experience building and maintaining demo environments or technical accelerator libraries for reuse across multiple engagements
Now Benefits (The Perks):
- Comprehensive medical, dental and vision plans for you and your dependents
- 401(k) Retirement Plan with Employer Match, 529 College Savings Plan, Health Savings Account, Life Insurance, and Long-Term Disability
- Competitive Compensation
- Training and development programs
- Major offices stocked with snacks and beverages
- Collaborative and cool culture
- Work-life balance and generous paid time off
Pay: Estimated Pay Range: $160,000 USD - $180,000 USD
Also note: Actual salary will be based on a variety of factors... but we should not include filler like "Actual salary will be based on a variety of factors..." maybe we can include as prose but it's not a specific number; it's still substantive. However the instruction: Prefer a few substantive sections over many thin ones. We could include Pay section with that sentence plus the range. It's okay.
Schedule: not present, omit.
Now we need to ensure we don't include boilerplate like EEO etc. Remove "Our Commitment" and accommodation note and recruitment agency note.
Now produce HTML fragment.
We'll have sections: About the role, Responsibilities, Requirements (maybe combine Required Qualifications as Requirements), Qualifications (Preferred Qualifications), Skills (maybe we can list technical skills from Required Qualifications? But we already have Required Qualifications includes skills. Could create Skills section summarizing technical proficiencies: Python, additional language, cloud data platforms, cloud provider, AI architectures, etc. But we might be duplicating. The instruction: Prefer few substantive sections over many thin ones. So maybe we combine Required Qualifications and Skills into one section called Requirements (or Qualifications). But we have both Required and Preferred; we could have Requirements (Required) and Qualifications (Preferred). That's two sections.
We also need Benefits and Pay.
Thus sections: About the role, Responsibilities, Requirements, Qualifications, Benefits, Pay.
Now ensure each section
for prose. Do NOT repeat job title as heading. Do NOT put Job ID/requisition numbers as headings. Preserve all substantive info; remove boilerplate (cookie/navigation/legal/EEO/equal-opportunity/scam-warning, duplicated lines, application instructions). Include a section only when posting has real specific content for it; never emit heading with filler/placeholder text. Prefer few substantive sections over many thin ones. We need to parse the posting: It starts with "Who is Trace3?" then description of company. Then "Street-Smart - Thriving in Dynamic Times", "Juice - The “Stuff” it takes to be a Needle Mover", "Teamwork - Humble, Hungry and Smart". Those seem like cultural values. Then "What You’ll Do As a Data Solutions Architect..." with responsibilities. Then "Required Qualifications", "Preferred Qualifications". Then "Actual salary will be based on a variety of factors..." then "Estimated Pay Range: $160,000 USD - $180,000 USD". Then "The Perks" list of benefits. Then "Our Commitment" (EEO etc) which is boilerplate to remove. Also "If you require a reasonable accommodation..." etc. Also recruitment agency note. We need to output sections: maybe About the role (company overview), Responsibilities (What You'll Do), Requirements (maybe combine Required Qualifications?), Qualifications (maybe Preferred?), Skills (maybe list of technical skills?), Benefits (The Perks), Pay (Estimated Pay Range). Schedule not present, so omit. We must not create sections with filler. So we need to ensure each section has substantive content. We need to decide which headings to use: About the role, Responsibilities, Requirements, Qualifications, Skills, Benefits, Pay. We must not repeat job title as heading. The job title is Data Solutions Architect (implied). We'll not put that as heading. We need to use
for each section heading. Inside sections, use
for prose,
- for lists.
We need to preserve all substantive info; do not invent or summarize away detail. So we need to include details from company overview, responsibilities, required qualifications, preferred qualifications, skills (maybe list of technical proficiencies), benefits, pay.
We must remove boilerplate: EEO statements, accommodation request, recruitment agency note, maybe also "Our Commitment" etc. Also remove duplicated lines.
We need to keep cultural values? Those are part of company overview maybe. Could include in About the role.
We need to ensure we don't include placeholder like "commensurate with experience" etc. Not present.
Now craft HTML.
Structure:
About the role
Trace3 is a leading Transformative IT Authority, providing unique technology solutions and consulting services to clients. Equipped with elite engineering and dynamic innovation, we empower IT executives and their organizations to achieve competitive advantage through a process of Integrate, Automate, Innovate. Our culture embodies the spirit of a startup with the advantage of a scalable business. Employees can grow their career and have fun while doing it! Trace3 is headquartered in Irvine, California, employs more than 1,200 people across the United States, with major field offices in Denver, Indianapolis, Grand Rapids, Lexington, Los Angeles, Louisville, Texas, San Francisco.
Maybe also include the cultural values: Street-Smart, Juice, Teamwork. Could embed as list. Better to put them as- within About the role.
But we need to avoid duplication.
Let's include a list of cultural traits.
Responsibilities
As a Data Solutions Architect, you will own the end-to-end lifecycle of technical proof work across the Data and Experiences BU. Your work will directly support Practice Directors, field SAs, and the Delivery Organization across the Intelligent Enterprise, Consumer Experiences, and Data and Analytics practices.
Then list duties: Pre-Sales and Client-Facing Technical Work, AI Innovation and Capability Development, Delivery Enablement, Thought Leadership and Team Contribution. Each with subpoints. We need to use- for any list of duties/requirements/benefits. So we can have a top-level
- with each major duty as
- , and inside each
- we can have further
- for subpoints? The instruction: Use
- for any list of duties/requirements/benefits. It doesn't forbid nested lists, but we can keep simple: each duty as
- and include prose inside. We'll need to preserve all substantive detail; not summarize away. So we need to include the details from each bullet. Let's extract responsibilities sections: Pre-Sales and Client-Facing Technical Work: - design, build, and present client-facing proofs of concept (POCs) and proofs of value (POVs) that demonstrate Trace3’s technical differentiation. These are not vendor-provided sandbox logins or generic demos. They are live, configured, Trace3-branded environments built on the client’s data, the client’s workflows, and the client’s integration points. You will own the scoping, architecture, build, and presentation of these assets. - lead AI capability demonstrations across the BU’s core technology plays, including agentic AI architectures, retrieval-augmented generation (RAG) systems, multimodal AI pipelines, MLOps platforms, and AI-native data and analytics stacks. - be the person in the room who can answer the question “can you show me that working?” with a yes – and then show it. - partner with Practice Directors and field SAs during active sales pursuits to define POC success criteria, scope minimum viable architectures, and ensure that every proof of concept is designed to answer a specific technical question – not to impress, but to advance the deal. AI Innovation and Capability Development: - be a visible, opinionated AI forward thinker within the BU. - track emerging AI capabilities across the vendor ecosystem, evaluate their relevance to Trace3’s client base, and translate that evaluation into actionable technical assets: working prototypes, architecture reference guides, and intake recommendations for the Accelerators build pipeline. - build reusable AI accelerator assets – prompt libraries, agent frameworks, RAG pipeline templates, evaluation harnesses, and fine-tuning playbooks – that reduce the time required to stand up AI capabilities from scratch on client engagements. - build these assets in collaboration with the TAMs, Practice Directors, and Delivery teams who will use them. - drive the Accelerators group’s contribution to the Pre-Sales Intelligence Evaluation Suite (CXE, DPE, SPE, IFE) – a set of AI-powered research evaluations that give Trace3 sellers an informed, opinionated starting position before the first client meeting. - build, test, and refine the agent prompts, research workflows, and output templates that make these evaluations repeatable and high-quality. Delivery Enablement: - build technical tooling that makes the Delivery Organization faster and more consistent. This includes configuration automation scripts that reduce platform stand-up time, automated UAT frameworks that catch issues early in the delivery lifecycle, and documentation automation pipelines that generate as-built artifacts as a byproduct of the delivery process rather than a manual effort at the end. - serve as the technical escalation path for Practice Directors and SAs who encounter questions they cannot answer – new vendor capabilities, integration edge cases, regulatory requirements that affect architecture decisions. - research, document, and communicate findings in a form that the requesting team can use immediately. Thought Leadership and Team Contribution: - contribute to the Accelerators group’s internal knowledge base, publishing technical briefs, architecture patterns, and lessons learned from every significant POC or accelerator build. - mentor junior team members and contribute to the continuous development of the team’s collective capability. - represent the Accelerators group in vendor technical briefings, partner advisory boards, and internal BU forums. Now Required Qualifications list: - Bachelor’s degree in computer science, engineering, mathematics, or a related field, or equivalent professional experience - 5 or more years of experience in solutions architecture, data architecture, or AI architecture with a track record of client-facing technical delivery - 3 or more years of hands-on experience building and deploying AI or machine learning solutions in production or near-production environments - Demonstrated experience designing and building POCs and POVs for enterprise clients, including scoping, architecture, build, and executive presentation - Proficiency in Python and at least one additional language (SQL, Scala, JavaScript, or R) - Hands-on experience with cloud data platforms (Snowflake, Databricks, or equivalent) and at least one major cloud provider (AWS, Azure, or GCP) - Working knowledge of modern AI architectures including large language models (LLMs), RAG systems, vector stores, knowledge graphs, and agentic frameworks - Outstanding communication and presentation skills with both technical and executive audiences, including the ability to present complex AI concepts to non-technical stakeholders - Strong organizational and time management skills with the ability to manage multiple concurrent POC and accelerator builds in a fast-moving environment Preferred Qualifications list: - Master’s degree in computer science, AI, machine learning, or a related field - Experience with MLOps platforms and practices (model versioning, monitoring, drift detection, retraining pipelines) - Experience with agentic AI frameworks (LangChain, LangGraph, AutoGen, CrewAI, or equivalent) - Experience with ETL and data pipeline architecture at scale (Apache Spark, Kafka, Flink, or equivalent) - Familiarity with CCaaS, UCaaS, or contact center AI platforms (Genesys, Five9, Cisco, or equivalent) - Relevant AI or cloud certifications (Azure AI Engineer, Google Cloud Professional ML Engineer, AWS Machine Learning Specialty, or equivalent) - Experience in a consulting or professional services environment where you have owned client-facing technical deliverables end-to-end - Experience building and maintaining demo environments or technical accelerator libraries for reuse across multiple engagements Now Benefits (The Perks): - Comprehensive medical, dental and vision plans for you and your dependents - 401(k) Retirement Plan with Employer Match, 529 College Savings Plan, Health Savings Account, Life Insurance, and Long-Term Disability - Competitive Compensation - Training and development programs - Major offices stocked with snacks and beverages - Collaborative and cool culture - Work-life balance and generous paid time off Pay: Estimated Pay Range: $160,000 USD - $180,000 USD Also note: Actual salary will be based on a variety of factors... but we should not include filler like "Actual salary will be based on a variety of factors..." maybe we can include as prose but it's not a specific number; it's still substantive. However the instruction: Prefer a few substantive sections over many thin ones. We could include Pay section with that sentence plus the range. It's okay. Schedule: not present, omit. Now we need to ensure we don't include boilerplate like EEO etc. Remove "Our Commitment" and accommodation note and recruitment agency note. Now produce HTML fragment. We'll have sections: About the role, Responsibilities, Requirements (maybe combine Required Qualifications as Requirements), Qualifications (Preferred Qualifications), Skills (maybe we can list technical skills from Required Qualifications? But we already have Required Qualifications includes skills. Could create Skills section summarizing technical proficiencies: Python, additional language, cloud data platforms, cloud provider, AI architectures, etc. But we might be duplicating. The instruction: Prefer few substantive sections over many thin ones. So maybe we combine Required Qualifications and Skills into one section called Requirements (or Qualifications). But we have both Required and Preferred; we could have Requirements (Required) and Qualifications (Preferred). That's two sections. We also need Benefits and Pay. Thus sections: About the role, Responsibilities, Requirements, Qualifications, Benefits, Pay. Now ensure each section
- for any list of duties/requirements/benefits. So we can have a top-level
- within About the role.
But we need to avoid duplication.
Let's include a list of cultural traits.