Artificial Intelligence (AI) Engineer

ABOUT TALENT MAP GLOBAL BPO INC:

Talent Map Global BPO, Inc. is a global talent solutions and business process outsourcing company connecting skilled professionals in the Philippines with growing North American businesses. We build dedicated offshore teams across technology, finance and accounting, marketing, and enterprise operations.

Our people-first culture is grounded in collaboration, integrity, continuous learning, and operational excellence. Team members gain meaningful exposure to international clients while building long-term careers in a supportive, performance-focused environment.

POSITION SUMMARY:

Driven AI Engineer who enjoys solving complex problems and applying artificial intelligence to meaningful operational challenges. In this role, you will design, develop, test, and integrate AI-enabled capabilities while collaborating directly with U.S.-based ASCENT engineers, software developers, product leaders, and mission experts. The ideal candidate combines a practical understanding of artificial intelligence and machine-learning with strong software-engineering fundamentals. You should be comfortable working in an evolving research and development environment, rapidly evaluating emerging technologies, developing prototypes, measuring solution performance, and transitioning successful concepts into secure and maintainable software products.

KEY RESPONSIBILITIES:

• AI Solution Development: Design, develop, test, and integrate AI-enabled software capabilities that address defined operational, business, and customer needs.
• Generative AI Applications: Develop applications using large language models and other foundation models, including conversational interfaces, knowledge assistants, content-generation tools, decision-support capabilities, and workflow automation.
• Retrieval-Augmented Generation: Build and improve retrieval-augmented generation solutions that securely connect approved data sources with generative
• Retrieval Design Judgement: Determine the appropriate retrieval strategy for each capability, including recognizing when a deterministic structured query over extracted, validated data is more appropriate than vector-based retrieval — for example, financial, accounting, and schedule questions requiring exact and reproducible answers.
• Prompt and Context Engineering: Develop, test, and maintain prompts, system instructions, context-management strategies, structured outputs, and reusable interaction patterns that improve model accuracy, consistency, and reliability.
• Prompt Governance: Maintain prompts and system instructions as versioned, reviewable artifacts with rollback capability and an audit record of what changed, when, and why.
• Model Integration: Integrate commercial, open-source, and internally developed AI models into software applications using approved APIs, software development kits, model-serving platforms, & cloud services.
• Model Selection and Adaptation: Evaluate and select commercially available, pretrained, and open-source models against defined accuracy, latency, cost, and safety criteria.
• Data Preparation and Pipelines: Build and maintain the pipelines that prepare approved data for AI development, evaluation, and operational use — collecting, extracting, cleaning, transforming, validating, and loading structured and unstructured sources including PDF, Office documents, Microsoft Project XML, and workbook inputs.
• AI Evaluation and Testing: Develop repeatable evaluation methods, test datasets, benchmarks, performance metrics to measure model accuracy, relevance, robustness, latency, safety, & operational effectiveness.
• AI Security and Responsible Use: Incorporate security, privacy, data protection, human oversight, explainability, and responsible AI practices throughout the solution lifecycle. Identify and help mitigate risks such as prompt injection, data leakage, model misuse, hallucinations, bias, and unreliable outputs.
• Packaging and Deployment Support: Work with the ASCENT DevSecOps and platform engineer to package, version, and monitor AI applications across approved development, test, and demonstration environments. Pipelines, environments, and production tenancy are owned by ASCENT; this role supplies the application-side packaging, configuration, and telemetry requirements.
• Application Development: Develop production-quality Python services, APIs, integrations, and supporting application components that enable AI capabilities to function within broader software solutions.
• Technical Evaluation and Prototyping: Assess emerging AI models, frameworks, development tools, and engineering approaches. Build prototypes and proofs of concept to determine technical feasibility, mission value, performance, security, and scalability.
• Cross-Functional Collaboration: Work directly with U.S.-based ASCENT team members to understand requirements, develop solutions, and maintain alignment across distributed teams.
• Communication and Coordination: Participate in recurring technical discussions, planning sessions, code reviews, demonstrations, and project-status meetings with U.S.-based ASCENT team members.
• Documentation and Knowledge Sharing: Create clear technical documentation, model cards, evaluation reports, architecture diagrams, operating procedures, reusable examples, and training materials.
• Data and Technology Protection: Follow applicable access restrictions, cybersecurity requirements, data-handling procedures, intellectual-property protections, and export-control guardrails associated

QUALIFICATIONS AND EXPERIENCE:

• Bachelor’s degree in computer science, artificial intelligence, machine learning, data science, software engineering, mathematics, statistics, or a related discipline, with equivalent relevant experience considered in place of a degree.
• Five or more years of experience in artificial intelligence, machine learning, data science, software engineering, or a related technical field, including hands-on development of AI-enabled applications.
• Proficiency in Python and experience developing maintainable, tested, and documented software.
• 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 through APIs, software development kits, or model-serving platforms.
• Experience developing APIs, services, or application integrations using frameworks such as FastAPI, Flask, Django, or comparable technologies.
• Familiarity with embeddings, semantic search, information retrieval, and vector-based data representations. Also with Git, including branching, pull or merge requests, code reviews, tagging, and collaborative development workflows. Software testing, debugging, dependency management, and secure development practices
• collaborative development workflows. Software testing, debugging, dependency management, and secure development practices.
• Experience integrating Azure OpenAI Service or a comparable enterprise AI service, including tool-calling, structured outputs, grounding, context management, token and cost management, and error handling.
• Understanding of AI-related security and reliability risks, including prompt injection, sensitive-data exposure, hallucinations, bias, model misuse, and ungrounded outputs.
• Ability to comply with company cybersecurity, acceptable-use, confidentiality, intellectual-property, export-control, and data-handling requirements.

DESIRED:

• Experience designing and implementing production-grade retrieval-augmented generation solutions.
• Experience with vector databases or search platforms such as PostgreSQL with pgvector, OpenSearch, Elasticsearch, Pinecone, Weaviate, Milvus, Chroma, or comparable technologies.
• Experience using machine learning or deep-learning frameworks and libraries such as PyTorch, TensorFlow, scikit-learn, Hugging Face, or comparable technologies.
• Experience developing AI agents, tool-using models, multi-step AI workflows, or human-in-the-loop automation capabilities. Using commercial or open-source large language models from providers or model families such as OpenAI, Anthropic, Google, Meta, Microsoft, Mistral, or comparable sources.
• Experience developing automated evaluation pipelines for generative AI applications, including groundedness, relevance, completeness, factual consistency, safety, and regression testing.
• Experience with model fine-tuning, parameter-efficient training, quantization, or optimization, and with MLOps tooling such as MLflow, Azure Machine Learning, or comparable model-registry, experiment-tracking, or feature-store platforms.
• Experience packaging and deploying AI applications using Docker, Kubernetes, or other container and orchestration technologies.
• Familiarity with CI/CD pipelines, infrastructure-as-code, automated security testing, DevSecOps practices.
• Experience developing data pipelines or working with relational databases, document stores, object storage, or streaming data. Orchestration tooling such as Azure Data Factory, Synapse pipelines, Airflow, Dagster, or Prefect, and with lakehouse storage or dbt style transformation.
• Experience working with U.S.-based customers, engineering teams, product organizations, or other international stakeholders.
• Familiarity with Agile software-development practices and distributed-team collaboration tools.
• Relevant technical certifications in artificial intelligence, machine learning, data engineering, cloud computing, or software development.

COMPENSATION AND BENEFITS:

• Base Salary - Competitive gross basic monthly salary, commensurate with the candidate’s qualifications, relevant experience, certifications, and specialized technical expertise
• Night Shift Differential - Provided in accordance with applicable Philippine labor requirements and company policy.
• Statutory Benefits - SSS, PhilHealth, Pag-IBIG, 13th-month pay, and applicable holiday pay in accordance with Philippine law.
• Allowances - Applicable de minimis or work-related allowances, subject to company policy and employment terms.
• Health Coverage - HMO coverage subject to the eligibility date and terms stated in the employment offer and company policy.
• Paid Leave - Vacation and sick leave benefits subject to eligibility, accrual rules, and company policy.

Pay: Php90,000.00 - Php100,000.00 per month

Benefits:

• Company events
• Health insurance
• Promotion to permanent employee
• Work from home

Work Location: Hybrid remote in Pampanga