Provectus

Junior AI/ML Engineer (GenAI, AWS)

Ukraine

Likely evergreen, first seen by us 25 days ago

Pay: Pay not listed
Work setting: Not stated
Employment: Full-time — employment source
Employment type Full-time
Employment type in the employer’s posting: Full-time
From the employer’s posting

Before you apply

New graduates: Entry levelJob title: Junior AI/ML Engineer (GenAI, AWS)

What you’ll work on

Full posting

Build and contribute to RAG system components under senior guidance
Write tests and help build evaluation harnesses for your features
Write production code across AI, backend services and data pipelines
Help integrate AI components into backend services and RESTful APIs
Support deployment of containerized systems to AWS with CI/CD

From the employer’s posting

Build and contribute to RAG system components under senior guidance, with growing autonomy.

Write tests and help build out evaluation harnesses for the features you work on.

Write production code across the stack (AI, backend services, data pipelines) with code review support.

Help integrate AI components into backend services and RESTful APIs.

Support deployment of systems to AWS (containerized, CI/CD), taking on more of this independently over time.

What you’ll bring

All qualifications

Core experience

Excellent communication and problem-solving skills.
Hands-on experience building or contributing to RAG systems, ideally in a production or near-production setting.
Experience in one of the industries: financial services, insurance, healthcare.
Practical experience with LLM APIs (Anthropic, AWS Bedrock, or OpenAI) in real projects.
Practical experience with one or more use cases from the following: NLP, LLMs, and Recommendation engines.
2+ years of software or ML engineering experience, including some exposure to production systems.

Qualification wording

Excellent communication and problem-solving skills.

Hands-on experience building or contributing to RAG systems, ideally in a production or near-production setting.

Experience in one of the industries: financial services, insurance, healthcare.

Practical experience with LLM APIs (Anthropic, AWS Bedrock, or OpenAI) in real projects.

Practical experience with one or more use cases from the following: NLP, LLMs, and Recommendation engines.

2+ years of software or ML engineering experience, including some exposure to production systems.

Benefits in the posting

Full benefits wording

Remote-friendly culture
Access to the latest AI tools and premium subscriptions
Private medical insurance or a budget for your medical needs
Paid sick leave, vacation, and public holidays
How we hire:
Employment type
Full-time

From the employer’s posting.

Apply at Provectus

Posting record

Report an error

Likely evergreenReposted 2 times since Sep 13, 2026. A role that keeps coming back is often kept open to collect applications rather than to fill one seat.

Status in our records: Live
First seen by us: Oct 10, 202625 days ago
Recorded sightings: 25
Last seen by us: Nov 4, 2026
Reposted: 2 times since Sep 13, 2026

These dates show when we found the posting. Check the employer’s website to confirm it is still accepting applications. We count a repost when the same title and location comes back as a new listing within 60 days of the last one coming down. Some hiring systems expire listings on a schedule, so repost rates vary by system.

How this job compares

Time since we first saw it

Day 25

Similar jobs usually come down between day 6 and day 69.

From 4,301 similar postings that came down. Coming down is not always a hire.

Provectus is hiring

5 open jobs

Open jobs by the week we first saw them, last 12 weeks.

ML Engineer hiring is picking up
Takes jobs down at a usual pace
60% of open jobs were reposted

Hiring record

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
Rust
TypeScript
AWS
S3
Spark
Airflow
Go

Where the posting names them

- Hands-on experience building or contributing to RAG systems, ideally in a production or near-production setting. - Solid engineering fundamentals; Python and/or TypeScript proficiency. Productive in an unfamiliar codebase with some ramp-up support. - Practical AWS experience (Lambda, S3, ECS, or similar); ready to grow into Bedrock and Bedrock AgentCore .

- Practical experience with one or more use cases from the following: NLP, LLMs, and Recommendation engines. - Experience in an additional language (Go, TypeScript, or Rust). - Experience with Apache Spark, Apache Airflow, Kafkа.

- Provectus is an AWS Premier Partner and an Anthropic Strategic Partner, working at the frontier of applied AI. We help enterprises turn Claude, agentic systems, and their own data into measurable business outcomes — through bespoke applications, managed services, and advisory engagements. With offices in North America, LATAM, and EMEA, we partner with clients worldwide. - Our work centers on two verticals — Financial Services & Insurance and Healthcare & Life Sciences — where we deploy five pre-built AI Blueprints: Submission Flow, Portfolio Lens, Asset Flow, Revenue Flow, and Evidence Lens. Each Blueprint rebuilds a critical business process front to back, shipped from working code and tuned to a client's specific book, regulators, and operating posture.

- Our work centers on two verticals — Financial Services & Insurance and Healthcare & Life Sciences — where we deploy five pre-built AI Blueprints: Submission Flow, Portfolio Lens, Asset Flow, Revenue Flow, and Evidence Lens. Each Blueprint rebuilds a critical business process front to back, shipped from working code and tuned to a client's specific book, regulators, and operating posture. - Our team holds 100+ AWS certifications, is Claude Code certified, and co-delivers Anthropic's Agentic SDLC program, Cowork Activation, and AI Blueprint engagements. Where this role sits

- Solid engineering fundamentals; Python and/or TypeScript proficiency. Productive in an unfamiliar codebase with some ramp-up support. - Practical AWS experience (Lambda, S3, ECS, or similar); ready to grow into Bedrock and Bedrock AgentCore . - Some experience with containers and CI/CD in real projects.

- Some hands-on exposure to the Claude ecosystem (Claude Code, CLAUDE.md, hooks, skills files) is a plus, or strong ability to ramp up quickly. - Practical experience with LLM APIs (Anthropic, AWS Bedrock, or OpenAI) in real projects. - 2+ years of software or ML engineering experience, including some exposure to production systems.

- Consulting, professional services, or other embedded customer-facing delivery. - AWS and Claude Code Certifications (or actively pursuing them). - A2A: Interest in agent-to-agent interoperability concepts.

- Help integrate AI components into backend services and RESTful APIs. - Support deployment of systems to AWS (containerized, CI/CD), taking on more of this independently over time. - Contribute to documentation, runbooks, and client handover materials.

- Remote-friendly culture - Internal training programs with full support for Claude, AWS, and other professional certifications, conference attendance - Career growth; we actively develop our engineers

- Experience in an additional language (Go, TypeScript, or Rust). - Experience with Apache Spark, Apache Airflow, Kafkа. - Experience with the Claude ecosystem — Claude Code, CLAUDE.md, hooks, skills files. Spec-driven development — writing the intent, constraints, and acceptance criteria before you let an agent build.

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Has Provectus posted this job before?

Yes. We’ve followed 2 other Junior AI/ML Engineer (GenAI, AWS) jobs there since September 2026. 2 came down, usually after about 24 days.

YerevanCame down after 42 days, first seen Sep 13
Place not statedCame down after 6 days, first seen Oct 3
This jobUp 25 days so far, first seen Oct 10

About the role

We file this job under ML Engineer, by the work the posting describes.

ML engineers put machine learning models into products. They write the code that trains, ships, serves and monitors models so a recommendation or prediction works for real users.

Postings ask for strong Python and software engineering, a framework such as PyTorch, cloud services, and more and more often experience with large language models.

A data scientist often works out which model to build; an ML engineer makes it run reliably in production.

US government figures for computer and information research scientists

Median yearly pay, May 2025: $140,300
Expected change, 2025 to 2035: 21.8% more jobsagainst 3.5% for all jobs

The government has no code for ML engineers, so these figures are for the closest group, computer and information research scientists.

Source: US Bureau of Labor Statistics, Occupational Employment and Wage Statistics (May 2025) and Employment Projections (2025 to 2035). Occupation code 15-1221.

Job description

View original posting ↗

Provectus is an AWS Premier Partner and an Anthropic Strategic Partner, working at the frontier of applied AI. We help enterprises turn Claude, agentic systems, and their own data into measurable business outcomes — through bespoke applications, managed services, and advisory engagements. With offices in North America, LATAM, and EMEA, we partner with clients worldwide.
Our work centers on two verticals — Financial Services & Insurance and Healthcare & Life Sciences — where we deploy five pre-built AI Blueprints: Submission Flow, Portfolio Lens, Asset Flow, Revenue Flow, and Evidence Lens. Each Blueprint rebuilds a critical business process front to back, shipped from working code and tuned to a client's specific book, regulators, and operating posture.
Our team holds 100+ AWS certifications, is Claude Code certified, and co-delivers Anthropic's Agentic SDLC program, Cowork Activation, and AI Blueprint engagements.

Where this role sits

You will work in a senior pod alongside an FDE, an FDX, and Senior AI Engineers — contributing to real delivery work while building toward independent ownership.

Requirements:

Mindset

Proactive and self-directed; you push for clarity rather than waiting for a ticket.
Excellent communication and problem-solving skills.
Comfortable with some ambiguity, with support from senior team members as you take on more.
B2+ English, comfortable collaborating across distributed, multicultural teams.

Technical depth

Hands-on experience building or contributing to RAG systems, ideally in a production or near-production setting.
Solid engineering fundamentals; Python and/or TypeScript proficiency. Productive in an unfamiliar codebase with some ramp-up support.
Practical AWS experience (Lambda, S3, ECS, or similar); ready to grow into Bedrock and Bedrock AgentCore .
Some experience with containers and CI/CD in real projects.
Exposure to evaluating non-deterministic systems — you've contributed to or run test/eval cycles, even if you haven't owned a full eval suite end-to-end.
Basic working knowledge of model/agent monitoring concepts.
Awareness of cost and latency trade-offs when working with LLMs.
Some hands-on exposure to the Claude ecosystem (Claude Code, CLAUDE.md, hooks, skills files) is a plus, or strong ability to ramp up quickly.
Practical experience with LLM APIs (Anthropic, AWS Bedrock, or OpenAI) in real projects.
2+ years of software or ML engineering experience, including some exposure to production systems.
Solid AI/ML foundations — you understand what the models do well enough to reason about common failure modes.

Nice to Have:

Experience in one of the industries: financial services, insurance, healthcare.
Consulting, professional services, or other embedded customer-facing delivery.
AWS and Claude Code Certifications (or actively pursuing them).
A2A: Interest in agent-to-agent interoperability concepts.
CI/CD pipeline experience (GitHub Actions, GitLab CI).
Practical experience with one or more use cases from the following: NLP, LLMs, and Recommendation engines.
Experience in an additional language (Go, TypeScript, or Rust).
Experience with Apache Spark, Apache Airflow, Kafkа.
Experience with the Claude ecosystem — Claude Code, CLAUDE.md, hooks, skills files. Spec-driven development — writing the intent, constraints, and acceptance criteria before you let an agent build.
MCP: you can say why an agent would prefer it to a REST integration, having authored a server is an additional plus.

Responsibilities:

Build and contribute to RAG system components under senior guidance, with growing autonomy.
Write tests and help build out evaluation harnesses for the features you work on.
Write production code across the stack (AI, backend services, data pipelines) with code review support.
Help integrate AI components into backend services and RESTful APIs.
Support deployment of systems to AWS (containerized, CI/CD), taking on more of this independently over time.
Contribute to documentation, runbooks, and client handover materials.
Participate in technical discussions and architectural decisions, with an eye toward taking on more of this independently.
Support model evaluation efforts and help investigate and improve failure modes.
Take on increasing ownership of components and technical decisions as you grow in the role.

What We Offer:

The chance to shape how leading enterprises across LATAM, Europe, and North America adopt AI, from strategy through first deployment

A forward-deployed model working in small, senior teams alongside FDE and FDX

A growing AI delivery practice where you help build the tooling and frameworks, not just use them

Remote-friendly culture

Internal training programs with full support for Claude, AWS, and other professional certifications, conference attendance

Career growth; we actively develop our engineers

Access to the latest AI tools and premium subscriptions

Long-term B2B collaboration

Private medical insurance or a budget for your medical needs

Paid sick leave, vacation, and public holidays

Equipment and all the tech you need for comfortable, productive work

How we hire:

Intro conversation. The role, your background and aspirations, tech questions.
Technical interview with live engineering sessions. Real problems, your own editor, you may use an LLM assistant
HR Interview. Soft skills and expectations
HM interview. Tech questions; a live engineering session is also possible

Employment type

Full-time

Source details