U.S. citizenship is required by the federal engagement supporting this role. Candidates must reside in and perform all work from within the United States. Work is remote, although occasional approved travel may be required. Visa sponsorship is not available.
Lanthos is hiring a hands-on GCP Generative AI Application Engineer to build and support applications using Gemini models through Vertex AI for a regulated public-sector program.
This is a junior-to-mid-level individual-contributor role. You will implement, test, monitor and document AI application features within established cloud, security and architecture patterns. You will work alongside senior technical leads and will not be expected to own the program’s enterprise architecture.
What you’ll do
Build and test Python services that integrate Gemini models and other approved models through Vertex AI.
Implement retrieval-augmented generation workflows, including ingestion, chunking, embeddings, retrieval, citations and grounded responses.
Develop containerized APIs and application components and deploy them to Cloud Run or another approved managed runtime.
Connect services to approved sources such as Cloud Storage, BigQuery, enterprise search indexes and internal APIs.
Create automated tests and evaluation checks for retrieval quality, groundedness, failure handling and response consistency.
Add application logging, monitoring and useful operational diagnostics.
Use Git-based development, code review and CI/CD practices.
Maintain implementation notes, test evidence and runbooks for security review and operational handoff.
Minimum qualifications
Two or more years of relevant software, data or machine-learning engineering experience, including at least one year of hands-on Google Cloud work.
Strong practical Python skills, including APIs, testing, error handling and data processing.
Hands-on experience personally building an LLM-enabled or RAG application with Gemini on Vertex AI beyond prompt-only experimentation.
Experience deploying a containerized application or service on Google Cloud.
Familiarity with Git, REST APIs and Docker.
A current Google Cloud Associate Cloud Engineer, Professional Cloud Developer or Professional Machine Learning Engineer certification.
Ability to explain personal technical contributions clearly and maintain useful documentation.
Preferred qualifications
Hands-on experience with Gemini on Vertex AI, Vertex AI Search or Vertex AI Vector Search.
Experience with Cloud Run, Cloud Storage or BigQuery.
Familiarity with embeddings, retrieval evaluation and LLM response-quality testing.
Familiarity with Google Agent Development Kit or another agent orchestration framework.
Experience using GitHub Actions, Cloud Build or another CI/CD platform.
Experience delivering software in a federal, public-sector or regulated environment.
Google Cloud Professional Cloud Developer or Professional Machine Learning Engineer certification.
Federal program requirements
Must be a U.S. citizen.
Must reside in and perform all work from within the United States.
Must be able to obtain and maintain the required MBI/Public Trust suitability determination.
Must be willing to complete required fingerprinting, identity verification, security and privacy training and applicable compliance checks.
Compensation and engagement
$70.00–$100.00 per hour, based on relevant experience and final assigned scope.
Independent-contractor engagement, anticipated up to 40 hours per week based on project needs and approved work.
Direct engagement with the individual or a candidate-owned corporation may be considered.
This contract engagement does not include company-sponsored employee benefits. No bonus, commission or equity compensation is currently offered.
Third-party staffing submissions are not accepted.
Applications are expected to remain open through August 21, 2026. The deadline may be extended if the position remains open.
Interview process
Initial conversation covering eligibility, availability and engagement expectations.
Practical technical interview focused on Python, cloud application delivery and an AI or RAG project the applicant personally implemented.
Team conversation covering communication, collaboration and regulated-program fit.
Lanthos LLC is an equal opportunity employer. The citizenship and suitability requirements above are imposed by the federal engagement supporting this position.
Pay: $70.00 - $100.00 per hour
Application Question(s):
- Do you meet the U.S.-citizenship requirement stated for this federal engagement? (Yes/No)
- Are you currently located in the United States and able to perform all work from within the United States? (Yes/No)
- Are you willing and able to complete an MBI/Public Trust suitability process, including fingerprinting and required compliance checks? (Yes/No)
- How many years of professional Python software-development experience do you have? Enter a number.
- Do you currently hold an active Google Cloud Associate Cloud Engineer, Professional Cloud Developer or Professional Machine Learning Engineer certification? (Yes/No)
- Provide the certification name, expiration date and a public credential link or credential ID.
- Which statement best describes your hands-on Gemini-on-Vertex-AI application experience? Choose one: production application; working pilot/internal application; personal project/coursework only; or no hands-on experience.
- In no more than 150 words, describe one Gemini-on-Vertex-AI application you personally built. Include your contribution, GCP deployment environment and how you tested retrieval or response quality.
- Are you available for a contract engagement anticipated up to 40 hours per week and comfortable proceeding within the posted $70–$100/hour range? (Yes/No)
Work Location: Remote
