Artificial Intelligence Senior Associate

We need to output HTML fragment only, with sections for headings where content exists. Must not repeat job title. Must not include Job ID etc. Must not include boilerplate like cookie/navigation/legal/EEO etc. Must remove application instructions, social media links? The instruction: "Remove cookie/navigation/legal/EEO/equal-opportunity/scam-warning boilerplate, duplicated lines, and application instructions." Social media links maybe considered navigation? Probably remove them. Also "Additional Info" about company purpose maybe not needed? It's not a standard heading; but we can keep as prose under maybe "About the Company"? Not a required heading. The instruction says use headings for sections like About the role, Responsibilities, Requirements, Qualifications, Skills, Benefits, Pay, Schedule. We have content: "About the Role" (we can treat as About the role). Then "What You'll Own" could be Responsibilities. Then "Skills Required" and "Skills Preferred" -> Skills. Then "Experience Required" and "Experience Preferred" -> Experience (maybe under Requirements or Qualifications). Then "Education Required" and "Education Preferred" -> Education (maybe under Qualifications). Then "Benefits" section present. No Pay or Schedule mentioned, so omit those sections. Also we have "Additional Info" about company purpose; could be omitted as not required heading, but we could keep as a paragraph under maybe "About the Company"? Not required; but we must preserve ALL substantive information; we cannot invent or summarize away detail. The "Additional Info" is substantive about company purpose, but not under a standard heading. We could include it as a

after the heading sections, maybe under a heading like "About the Company"? But instruction says use headings for those specific ones; we could still add other headings if needed? It says "use

for section headings (e.g. About the role, Responsibilities, Requirements, Qualifications, Skills, Benefits, Pay, Schedule)." It gives examples but not exclusive; we could add other headings if needed, but better to stick to those. However we must preserve all substantive info; we could put the Additional Info as a

under a generic section like "About the Company" but that's not in list; maybe we can just include it as a

after the Benefits section without a heading. That's acceptable: preserve info as prose. We must remove duplicated lines, boilerplate like social media links, AI & Hiring Disclosure (that's legal/EEO? It's about AI usage in hiring; could be considered legal boilerplate; we should remove it). Also remove "To view all of our open positions go to:" etc. Also remove "Follow us on Twitter..." etc. Also remove "AI & Hiring Disclosure" block. We must keep Benefits content. Now structure:

About the role

We are seeking a high-impact AI/ML Engineer to build intelligent data products that turn complex, high-volume engineering information into trusted, actionable insight. You will work across applied machine learning, generative AI, data platforms, and cloud engineering to deliver production systems used for search, traceability, analytics, and decision support. This role is ideal for an engineer who can move from architecture to implementation to operational ownership, and who enjoys solving ambiguous problems where data quality, scale, and reliability matter.

Responsibilities

• Architect, build, and operate reliable data products that ingest and transform diverse structured and unstructured information at enterprise scale.
• Create resilient orchestration and delivery patterns for batch and near-real-time workloads, with clear observability, alerting, and operational runbooks.
• Develop production Retrieval-Augmented Generation systems that combine semantic retrieval, structured data, and grounded responses for high-value engineering use cases.
• Design agentic AI workflows that decompose complex questions, select the right data sources and tools, validate results, and return explainable answers with citations.
• Develop and evaluate embedding, document-understanding, and multimodal inference workflows, balancing quality, latency, scalability, and cost.
• Lead cloud architecture, containerization, infrastructure-as-code, and CI/CD practices for secure, repeatable deployment across environments.
• Own system reliability from design through production: investigate incidents, profile performance, eliminate failure modes, and improve capacity planning.
• Deliver intuitive analytics experiences and decision-support tools that make complex technical data useful to engineers, program teams, and leadership.
• Establish data quality, lineage, validation, and governance practices so users can understand where information came from and how much to trust it.
• Build incremental, restartable processing with checkpointing and recovery strategies that protect data integrity during long-running or partially failed workloads.

Skills

Required: Python, SQL, Artificial Intelligence & Expert Systems, GCP, API, Software Testing, Data Analysis

Preferred: Data/Analytics dashboards, Data Collection, Data Integrity, Java, Data Acquisition, Data Conversion

Alternatively we could use

for each list. The instruction: Use
• for any list of duties/requirements/benefits. For skills, it's a list; we can do
  • Python
  ... etc. But we have required and preferred; we could separate. Better:

  Skills Required

  ...
  and

  Skills Preferred

  ...
  . But the instruction says use headings like Skills (maybe combine). We'll do separate headings for clarity. But we must not create headings with filler text; we have real content. Similarly for Experience: we have Required and Preferred. Education: Required and Preferred. We'll create sections:

  Experience Required

  ...

  Experience Preferred

  ...

  Education Required

  Bachelor's Degree

  Education Preferred

  Certification Program

  But the instruction says use headings like Requirements, Qualifications, Skills, Benefits. Could also combine Experience Required/Preferred under Requirements or Qualifications. However we must preserve all info; we can keep separate headings as they are substantive. But the instruction: "use

  for section headings (e.g. About the role, Responsibilities, Requirements, Qualifications, Skills, Benefits, Pay, Schedule)." It suggests we could use Requirements and Qualifications as headings. We could put Experience under Requirements, Education under Qualifications. That would reduce number of headings. Let's do that. Thus:

  About the role

  (as given)

  Responsibilities

  Requirements

  (contains Experience Required and maybe Skills Required? But Skills separate heading) Better: Keep Skills separate heading. Thus:

  Requirements

  (Experience Required)

  Qualifications

  (Education Required)

  Skills

  (Skills Required and Preferred maybe separate subheadings? Could do

  but not allowed? Only h3 for section headings. Could embed inside

  . That's fine. Thus:

  Requirements

  ... experience required items ...

  Qualifications

  Bachelor's Degree

  Certification Program (preferred)

  but we need to differentiate preferred. Could add note. Alternatively we could have

  Experience

  and

  Education

  . But the instruction examples include Requirements, Qualifications. We'll follow that. Thus:

  Requirements

  ... experience required items ...

  Experience Preferred

  maybe as separate heading under Requirements? Could be

  Experience Preferred

  but that's similar to Requirements; maybe we can combine with note. But to preserve all info, we need to list both required and preferred experience. Could do:

  Experience

  Required: ...

  Preferred: ...

  Similarly for Education. Thus we reduce headings. Let's decide final structure: - About the role - Responsibilities - Experience - Education - Skills - Benefits That covers all. Now extract content. Experience Required bullet list: - 5+ years of experience building and operating production software, data, or machine learning systems, with strong Python and SQL skills. - Professional experience with cloud platforms, managed data services, object storage, containers, and distributed workloads. - Experience designing and operating scalable data pipelines or distributed processing systems for large and evolving datasets. - Hands-on experience applying large language models to real products, including prompt design, structured outputs, tool use, evaluation, and production monitoring. - Strong understanding of embeddings, vector retrieval, RAG architecture, model limitations, and techniques for improving answer quality and faithfulness. - Experience with software engineering fundamentals: testing, code review, version control, CI/CD, observability, and secure development practices. - Demonstrated ability to diagnose difficult production problems using measurable evidence, experimentation, profiling, and disciplined root-cause analysis. - Experience with workflow orchestration, job scheduling, or reliable batch execution frameworks Experience Preferred bullet list: - Experience with agentic AI frameworks, tool-using systems, or multi-step reasoning workflows. - Experience with managed generative AI, model serving, batch inference, or vector database platforms. - Experience with infrastructure-as-code and automated cloud delivery. - Experience extracting meaning from complex documents, legacy formats, technical diagrams, or other semi-structured content at scale. - Experience in automotive, manufacturing, safety-critical, systems engineering, or another technically regulated domain. - Experience building internal analytics products or developer-facing tools that translate complex data into clear decisions. Education Required: Bachelor's Degree Education Preferred: Certification Program Skills Required list: Python, SQL, Artificial Intelligence & Expert Systems, GCP, API, Software Testing, Data Analysis Skills Preferred list: Data/Analytics dashboards, Data Collection, Data Integrity, Java, Data Acquisition, Data Conversion Now Benefits list: - Medical and Dental (FastTek pays majority of the medical program) - Vision - Personal Time Off (PTO) Program - Long Term Disability (100% paid) - Life Insurance (100% paid) - 401(k) with immediate vesting and 3% (of salary) dollar-for-dollar match - lucrative employee referral program - employee recognition culture - FastTek Global was named one of the Top Work Places in Michigan by the Detroit Free Press in 2013, 2014, 2015, 2016, 2017, 2018, 2019, 2020, 2021, 2022, and 2023! We should keep the bullet points as list items. Now we need to remove duplicated lines: there is none. Now produce HTML. We'll wrap each section in

  and then

  • ...

  for lists,

  for prose. For Experience and Education we have both required and preferred; we could do

  Required: ...

  Preferred: ...

  inside the section. Let's craft. Experience section:

  Experience

  Required:

  • 5+ years of experience building and operating production software, data, or machine learning systems, with strong Python and SQL skills.
  • Professional experience with cloud platforms, managed data services, object storage, containers, and distributed workloads.
  • Experience designing and operating scalable data pipelines or distributed processing systems for large and evolving datasets.
  • Hands-on