AI Engineer (LLMs & Generative AI)

About Us

InterScripts is a Information Technology business based in Chantilly, VA and established in 2017 providing technology and platform enabled services and solutions. Historically, we have enabled our customers to realize the most value from their technology and resources through our Managed Services, Archival Solution, EHR, ERP, Advisory, Virtual Care, Technology, Application Development, and Cybersecurity services.

In addition, InterScripts has substantial experience in providing Technology and Platform Enabled solutions to commercial, public sector, and government entities. We are an ISO 27001, 9001 CMMI 3 and SOC 2 certified organization, signifying our ability to lower the risks for our clients’ application modernization efforts, custom development, support, operations, and MSP projects.

Job Description

AI/ML Engineer - Generative AI- Bilingual

Location: Medellín | Onsite

Role Overview

We are seeking a highly skilled AI Engineer (LLMs & Generative AI) to design, build, and scale enterprise-grade AI systems powered by large language models, generative AI technologies, and massive datasets.

This role is ideal for an experienced engineer with hands-on expertise deploying LLM-powered applications in production environments, implementing AI guardrails and responsible AI practices, and building scalable AI solutions across complex enterprise ecosystems.

You will play a key role in shaping the organization’s AI capabilities — from model orchestration and retrieval systems to safety, governance, and performance optimization — while collaborating with global teams in a fast-paced, innovation-driven environment.

We are especially interested in bilingual (English/Spanish) professionals who can effectively collaborate across technical and business stakeholders internationally.

Key Responsibilities

LLM & Generative AI Development

• Design, develop, and deploy applications powered by LLMs and generative AI models.
• Build AI solutions for enterprise search, document intelligence, summarization, conversational AI, workflow automation, and knowledge management.
• Work with both commercial and open-source LLMs based on business and technical requirements.
• Optimize prompts, model parameters, inference pipelines, and latency/cost tradeoffs.
• Develop scalable APIs and backend services supporting AI-driven applications.

AI Guardrails & Responsible AI

• Design and implement AI guardrails to ensure safe, reliable, and policy-compliant outputs.
• Develop mechanisms for:
• Hallucination mitigation
• Content filtering and moderation
• Prompt injection defense
• Output validation and verification
• Access and usage controls
• Build evaluation frameworks to measure safety, groundedness, consistency, accuracy, and model reliability.
• Partner with security and compliance teams to align AI systems with enterprise governance standards.

Massive Data & RAG Systems

• Work with large-scale structured and unstructured enterprise datasets.
• Design and optimize Retrieval-Augmented Generation (RAG) pipelines.
• Build workflows for:
• Data ingestion and preprocessing
• Chunking and embeddings
• Vector indexing and semantic retrieval
• Context ranking and relevance optimization
• Collaborate with data engineering teams to ensure scalability and high performance across distributed systems.

Model Orchestration & Evaluation

• Implement orchestration strategies across multiple models and APIs.
• Develop fallback, routing, and hybrid model strategies to optimize performance and cost.
• Define and monitor evaluation metrics for model quality and reliability.
• Conduct benchmarking, A/B testing, and continuous optimization of AI systems.

Engineering & Deployment

• Build production-grade AI systems using modern software engineering best practices.
• Integrate AI services into enterprise applications, APIs, and workflows.
• Support CI/CD pipelines, testing, versioning, observability, and monitoring for AI platforms.
• Ensure systems are scalable, secure, observable, and cost-efficient.

Cross-Functional Collaboration

• Partner with product, engineering, data, and business teams to translate requirements into AI-driven solutions.
• Communicate technical concepts clearly to global stakeholders.
• Contribute to architecture decisions, reusable AI frameworks, and technical documentation.
• Collaborate effectively in English-speaking international environments.

Requirements

• Bachelor’s or Master’s degree in Computer Science, Artificial Intelligence, Machine Learning, Data Science, or related field.
• 5+ years of experience in software engineering, AI, or machine learning roles.
• Strong hands-on experience building applications using LLMs and generative AI technologies.
• Experience working with large-scale enterprise data environments.
• Deep understanding of: Prompt engineering RAG architectures AI evaluation frameworks AI safety and guardrails Strong programming expertise in Python and backend development. Experience designing and deploying production-ready AI systems.

Fluent English Communication Skills (required).

Bilingual English/Spanish communication skills preferred.

Preferred Technical Experience

• Experience with:
• LangChain
• LlamaIndex
• Semantic Kernel
• Hugging Face ecosystem
• OpenAI, Azure OpenAI, and Anthropic APIs
• Experience with vector databases such as:
• Pinecone
• Weaviate
• FAISS
• Knowledge of:
• Embeddings and semantic search
• Model fine-tuning and adaptation techniques
• AI observability and monitoring tools
• Familiarity with:
• AWS, Azure, or GCP
• Databricks
• Apache Spark
• Distributed data systems
• Docker and Kubernetes
• MLOps pipelines and AI lifecycle management
• Understanding of AI security, privacy, governance, and enterprise access controls.

Preferred Certifications

• Microsoft Certified: Azure AI Engineer Associate
• AWS Certified Machine Learning – Specialty
• Google Professional Machine Learning Engineer
• Databricks Machine Learning Certification
• TensorFlow Developer Certificate
• Certifications in Responsible AI, AI Governance, or Data Engineering

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