Junior AI/ML Engineer (GenAI, AWS)

Talanto; Philippines; Hybrid; PHP 3,364,000 - 12,128,000; Full time

Benefits offered by this job

Remote-friendly culture

Professional certifications

Job summary

Talanto is seeking a senior AI/ML engineer to build and ship production GenAI systems, focusing on Claude-based workflows and agentic AI solutions.

You will work in a senior pod, paired with experienced engineers, delivering cloud-native data pipelines, LLM integrations, and evaluation harnesses across global customers.

Qualifications

• 2+ years of software or ML engineering experience; production systems exposure.
• Solid fundamentals; Python and/or TypeScript proficiency.
• Hands-on production experience with the Claude ecosystem and related tooling.
• Experience with LLM APIs (Anthropic, AWS Bedrock, OpenAI).
• Awareness of cost and latency trade-offs when working with LLMs.

Responsibilities

• Work in a pair with an FDE and an FDX to deliver features.
• Build and ship production GenAI systems into customer environments.
• Develop and optimize RAG systems for real use cases.
• Write production code across AI, backend services, and data pipelines.
• Implement LLMOps and AgentOps like tracing, prompts, and testing.

Skills

Python

TypeScript

AWS experience

Claude ecosystem

LLM APIs

CI/CD

Containerisation

Problem solving

English communication

MCP mindset

Tools

Claude Code

CLAUDE.md

AWS Bedrock

GitHub Actions

Job description

Important: if an employer asks you to log into their system via iCloud or Google, send a code, an SMS or Telegram password, run some code, or install software — refuse. These are signs of fraud.

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.

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.

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

Hands-on production 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 — is a strong plus. MCP: you can say why an agent would prefer it to a REST integration. Having authored a server is a plus.

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

Responsibilities

Work in a pair with an FDE and an FDX.

Build and ship production GenAI systems into the customer’s environment (cloud-native data, LLM-based, and agentic AI solutions).

Build and optimize RAG systems for production use cases

Build the evaluation harness before you build the feature.

Write production code across the stack — AI, backend services, data pipelines. We choose tools to fit the customer.

Integrate AI components into backend services and RESTful APIs

Take systems to production on AWS (GCP or Azure where the customer requires it): containerised, CI/CD. Implement LLMOps and AgentOps practices: agent tracing, prompt and version management, cost and latency monitoring, regression testing, drift detection

Start from the blueprint, contribute to enablement and handover: clear documentation, runbooks, and pairing with the client engineers who will inherit the system. Feed reusable components and lessons back into the Blueprints

Participate in technical discussions and architectural decisions

Conduct model evaluation, improve failure modes you find, optimize model performance, efficiency, and reliability

Mentor junior and mid-level AI engineers, conduct code reviews and share knowledge across the team through documentation, presentations, and workshops.

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

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

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

4808-17333$ /month

4808 $ 25%

8999 $ median

17333 $ 75%

The range shows the lower and upper market bands: 25% of vacancies pay below the first value, the median is the typical salary, and 75% marks the upper band.