Time since we first saw it
Day 70
Similar jobs usually come down between day 4 and day 77.
Well past UKG’s usual: its jobs come down by about day 22.
From 51 similar postings that came down, and 49 of UKG’s. Coming down is not always a hire.
Staff AI & Machine Learning Engineer
Reads like an AI Engineer role: building products on existing AI models.
Noida, UP, IN
Live, first seen by us 70 days ago- Pay
- Pay not listed
- Work setting
- Not stated
- Employment
Full-time — employment source
Employment type in the employer’s posting: FULL_TIME
From the employer’s posting
What you’ll work on
Full postingLead architecture and delivery of cloud micro-services in Python
Own GenAI initiatives end-to-end, from data strategy to continuous optimization
Set engineering standards and enforce them through code reviews and mentoring
Define SLOs, monitor telemetry, and lead incident response and root-cause analyses
Scope epics with product and align roadmaps across functions
From the employer’s posting
Lead architecture and delivery of cloud micro-services in Python
Own GenAI initiatives end-to-end—data strategy, model selection or fine-tuning, evaluation, deployment, and continuous optimization
Set engineering standards for reliability, security, performance, CI/CD, and observability; enforce them through rigorous code reviews and mentoring
define SLOs, monitor telemetry, lead incident response, and run blameless root-cause analyses
scope epics with product, align roadmaps
Posting record
Report an error- Status in our records
- Live
- First seen by us
- Sep 4, 202670 days ago
- Recorded sightings
- 277
- Last seen by us
- Nov 13, 2026
These dates show when we found the posting. Check the employer’s website to confirm it is still accepting applications.
How this job compares
UKG is hiring
13 open jobs
Open jobs by the week we first saw them, last 12 weeks.
- Hiring at a steady pace
- Takes jobs down quickly
See how this role fits your experience
Add your resume and we’ll mark which of these tools you already use, and point out anything in the posting that could rule you out.
- Python
- SQL
- AWS
- Azure
- BigQuery
- Docker
- GCP
- Kubernetes
- NoSQL
- Terraform
- FastAPI
- Streamlit
Where the posting names them
Lead architecture and delivery of cloud micro-services in Python with LangChain, LangGraph, ADK, MCP, A2A and web-first frameworks such as FastAPI, Streamlit, Gradio, FastHTML. Own GenAI initiatives end-to-end—data strategy, model selection or fine-tuning, evaluation, deployment, and continuous optimization for structured reasoning, autonomous planning, image/video generation, and real-time “live-mode” interactions. Set engineering standards for reliability, security, performance, CI/CD, and observability; enforce them through rigorous code reviews and mentoring. Drive cross-functional execution—scope epics with product, align roadmaps, and deliver high-value features on time while proactively mitigating risk. Champion production excellence—define SLOs, monitor telemetry, lead incident response, and run blameless root-cause analyses in a true DevOps model. Mentor and multiply talent—coach engineers, run lightning talks, and foster a culture of candid feedback and continuous learning. Document and broadcast decisions through clear design docs and architecture reviews that scale knowledge across the organization. Bachelor's degree in CS, Engineering, or equivalent practical experience (Master's preferred). 6+ years of professional Python development, including large-scale, production AI/ML systems. Demonstrated experience in building applications on foundation-model APIs and to use AI daily in your workflow (GitHub Copilot, Windsurf/Cursor, Claude Code, etc.). Hands-on cloud experience (GCP, AWS, or Azure) plus containerisation (Docker, Kubernetes) and modern CI/CD pipelines. Demonstrated leadership in setting technical direction and mentoring engineers. Deep expertise with LangChain, LangGraph, ADK, MCP, A2A and multimodal model orchestration. Experience in Next-gen AI coding agents/IDEs such as Cursor, Windsurf, Claude Code. Knowledge of GCP services (Vertex AI, BigQuery, GKE, Kubeflow), Terraform, GitHub Actions, Docker, Kubernetes. Knowledge of Vector, SQL, and NoSQL data stores; streaming frameworks; distributed-systems concepts; advanced observability and SRE practices. A self-starter who devours research papers and turns them into production-ready prototypes. Energized by ambiguity and full ownership in an AI-first culture; you instinctively raise the bar for those around you. Inclusive, candid, and relentlessly customer-obsessed. Please add a link in your résumé (GitHub repo, blog post, Kaggle entry, etc.) that shows something you taught yourself in the last six months and why it excited you.
Your next step
Complete your application on apply.ukg.com. The employer’s form will show what is required.
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Demand for AI Engineer roles
New AI Engineer postings at the employers we follow are up 134% over the last 6 weeks compared with the 6 before.
Each bar is one week of new postings. The darkest bars are the last 6 weeks.
Counted from the hiring pages we’ve followed for at least five weeks, so employers we add don’t look like growth. Updated weekly.
About the role
We file this job under AI Engineer, by the work the posting describes.
AI engineers build products on top of AI models that already exist, most often large language models: they connect a model to a company's data and tools and ship the assistants, agents and search features people use.
Postings ask for strong Python or TypeScript, experience with model APIs, retrieval and agent frameworks, and ways to test whether the model's answers are good enough.
An ML engineer trains and serves models; an AI engineer usually starts from a model someone else trained and builds the product around it, though titles often mix the two.
Job description
Lead architecture and delivery of cloud micro-services in Python with LangChain, LangGraph, ADK, MCP, A2A and web-first frameworks such as FastAPI, Streamlit, Gradio, FastHTML. Own GenAI initiatives end-to-end—data strategy, model selection or fine-tuning, evaluation, deployment, and continuous optimization for structured reasoning, autonomous planning, image/video generation, and real-time “live-mode” interactions. Set engineering standards for reliability, security, performance, CI/CD, and observability; enforce them through rigorous code reviews and mentoring. Drive cross-functional execution—scope epics with product, align roadmaps, and deliver high-value features on time while proactively mitigating risk. Champion production excellence—define SLOs, monitor telemetry, lead incident response, and run blameless root-cause analyses in a true DevOps model. Mentor and multiply talent—coach engineers, run lightning talks, and foster a culture of candid feedback and continuous learning. Document and broadcast decisions through clear design docs and architecture reviews that scale knowledge across the organization. Bachelor's degree in CS, Engineering, or equivalent practical experience (Master's preferred). 6+ years of professional Python development, including large-scale, production AI/ML systems. Demonstrated experience in building applications on foundation-model APIs and to use AI daily in your workflow (GitHub Copilot, Windsurf/Cursor, Claude Code, etc.). Hands-on cloud experience (GCP, AWS, or Azure) plus containerisation (Docker, Kubernetes) and modern CI/CD pipelines. Demonstrated leadership in setting technical direction and mentoring engineers. Deep expertise with LangChain, LangGraph, ADK, MCP, A2A and multimodal model orchestration. Experience in Next-gen AI coding agents/IDEs such as Cursor, Windsurf, Claude Code. Knowledge of GCP services (Vertex AI, BigQuery, GKE, Kubeflow), Terraform, GitHub Actions, Docker, Kubernetes. Knowledge of Vector, SQL, and NoSQL data stores; streaming frameworks; distributed-systems concepts; advanced observability and SRE practices. A self-starter who devours research papers and turns them into production-ready prototypes. Energized by ambiguity and full ownership in an AI-first culture; you instinctively raise the bar for those around you. Inclusive, candid, and relentlessly customer-obsessed. Please add a link in your résumé (GitHub repo, blog post, Kaggle entry, etc.) that shows something you taught yourself in the last six months and why it excited you.
Source details
Source notes
Source excerptsSelected passages from the saved posting. Check the full description for conditions and exceptions.
- Pay
No pay amount identified in the saved description.
- Location & working pattern
Noida, UP, IN
Working pattern and location restrictions need checking in the full posting.
- Work authorization
No clear work-authorization passage found. Eligibility is unconfirmed.