AI Engineer: Build Scalable AI-Powered Solutions

Talent Map Global BPO Inc.

Angeles

On-site

PHP 1,200,000 - 1,800,000

Full time

6 days ago

Be an early applicant

Application generator

Don’t send a generic resume — generate a resume and cover letter tailored to this exact role.

Get past ATS filters

Benefits offered by this job

Base salary

Night shift differential

Statutory benefits

Allowances

Health coverage

Paid leave

Job summary

Talent Map Global BPO, Inc. seeks a driven AI Engineer to design, develop, and integrate AI-enabled capabilities, collaborating with U.S.-based ASCENT engineers, software developers, and mission experts.

You will work in an evolving R&D environment, prototype rapidly, measure performance, and transition concepts into secure software products. The role emphasizes practical AI/ML knowledge, strong software engineering fundamentals, and building production-grade Python services within broader

Qualifications

Bachelor's degree in a related field or equivalent experience.
5+ years of AI/ML or data science experience with software development.
Proficiency in Python with tested software development practices.
Experience with generative AI frameworks or orchestration tools such as LangChain, LangGraph, LlamaIndex, Semantic Kernel, or comparable technologies.
Experience integrating large language models, foundation models, or AI services into software applications via APIs, SDKs, or model-serving platforms.
Experience developing APIs/ services using FastAPI, Flask, Django, or comparable frameworks.
Familiarity with embeddings, semantic search, vector representations, Git, testing, debugging, and secure development practices.
Experience integrating Azure OpenAI Service or comparable enterprise AI services, including tool-calling, structured outputs, grounding, context management, and cost handling.

Responsibilities

Design, develop, test, and integrate AI-enabled software capabilities that address defined operational and customer needs.
Develop applications using large language models and foundation models, including conversational interfaces, content-generation tools, and workflow automation.
Build and improve retrieval-augmented generation solutions connecting data sources with generative AI.
Determine retrieval strategies, balancing deterministic queries and vector-based retrieval.
Develop, test, and maintain prompts, system instructions, and context-management strategies for model accuracy and reliability.
Integrate AI models into software apps via approved APIs, SDKs, and model-serving platforms.
Build and maintain data pipelines for AI development, evaluation, and operation.
Develop evaluation methods, benchmarks, and metrics for model quality and safety.
Incorporate security, privacy, and responsible AI practices throughout the lifecycle.
Develop production-quality Python services, APIs, and integrations enabling AI features in broader solutions.