4 publicaciones de empleo destacadas de full stack software engineer, observability en desde casa (¡Están contratando!)

Lead AI Integration Engineer
3Pillar —Desde casa
- Tiempo completo
- Home Office (Desde casa)
- Azure
- Inglés
- Java
- Permiso de maternidad y paternidad
- Seguro de vida
12d
Lead Site Reliability Engineer
EPAM Systems, Inc. —Desde casa
- Home Office (Desde casa)
- Azure
- Administración de personal
- DevOps
- Plan de adquisición de acciones empresariales
Senior DevOps Engineer
EPAM Systems, Inc. —Desde casa
- Home Office (Desde casa)
- DevOps
- Inglés
- Vacaciones adicionales o permisos con goce de sueldo
1h
Lead DevOps Engineer
EPAM Systems, Inc. —Desde casa
- Home Office (Desde casa)
- Administración de personal
- DevOps
- Inglés
- Vacaciones adicionales o permisos con goce de sueldo
1h

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Lead AI Integration Engineer

3Pillar -
Desde casa

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Información del empleo

Tiempo completo
Hace 12 días

Beneficios

Permiso de maternidad y paternidad
Seguro de vida

Cualificaciones

Modelos de inteligencia artificial
TensorFlow
Azure
Derecho
Ingeniería de software
PyTorch
C#
Inglés
Java
JavaScript
Desarrollo de software
Seguridad
Python

Descripción completa del empleo

3Pillar is an AI transformation partner on a mission to help enterprises build the AI-native products and intelligent agents that will define the next era of business. With teams across North America, Europe, Latin America, and Asia, we work with the most ambitious companies in financial services, healthcare, media, and technology — helping them move faster, modernize boldly, and compete on their own terms. Our HelixAI platform and Helix Pods delivery model put our engineers at the center of real agentic transformation — doing work that is open, portable, and built to last. We are building the future of enterprise AI.

Lead, AI Engineering

As a Lead, AI/ML Engineer at 3Pillar, you will lead end-to-end AI solutions for our clients. You will work on complex AI/ML problems, contribute to architecture decisions, and ship agentic, LLM-based systems and ML solutions in production.

This role sits at the intersection of backend engineering and applied AI. You are someone who can seamlessly connect APIs, orchestrate data flows, and build Retrieval-Augmented Generation (RAG) systems, all while maintaining rigorous data privacy standards. In an era defined by AI, you will be the force that turns theoretical AI concepts into production-ready features.

Key Responsibilities

Design, build, and deploy intelligent backend services using Python and Azure AI Foundry.
Consume Force Account outputs by API, ensuring the system can accurately display and act on data classification and extraction.
Engineer and optimize Retrieval-Augmented Generation (RAG) pipelines over Standard Operating Procedures (SOPs) to provide contextual, accurate, and actionable insights to users.
Deliver assistive intelligence directly on the case, seamlessly integrating AI outputs into the end-user's workflow.
Design and strictly enforce a redact-before-model discipline, ensuring that all Personally Identifiable Information (PII) is stripped from payloads before data ever reaches a foundational model.
Collaborate with product, design, and engineering teams to shape AI features and translate business goals into technical execution.
Proactively identify AI-driven automation and product improvement opportunities, building prototypes to prove value.
Mentor junior engineers and champion secure, responsible AI coding practices within your team.
Troubleshoot AI-specific technical challenges, including prompt injection risks, model latency, and data leakage.
Guide team members on model selection, evaluation, fine-tuning, and Gen AI usage.
Actively evaluate emerging LLM tooling, agentic frameworks, and open-source developments for applicability to client engagements.
Own the architecture of the team's agentic and LLM systems — agent orchestration, tool integration (e.g., Model Context Protocol), retrieval, and human-in-the-loop design.
Design and implement evaluation frameworks for LLM and agentic systems — covering correctness, boundary, and intent checks — as a standard part of delivery.
Drive adoption of the agentic SDLC across the team: select and roll out AI engineering tools, define usage and governance standards, and measure their impact on delivery velocity and quality.
Establish responsible-AI and evaluation frameworks for agentic systems — guardrails, safety testing, human oversight, and model governance.

Minimum Qualifications

A minimum of 8+ years of experience in software engineering, with at least 2+ years of hands-on experience integrating LLMs and building AI-driven applications.
Demonstrated experience architecting and deploying LLM-based or agentic systems in production, including prompt design, retrieval architecture, and tool/function calling (e.g., MCP)
Hands-on experience with leading LLMs and APIs, including OpenAI, Google Gemini, and Anthropic Claude.
Experience evaluating and selecting open-source and proprietary LLMs (e.g., OpenAI via Azure AI Foundry) based on accuracy, latency, scalability, cost, and overall performance for production AI solutions.
Knowledge of vector stores, embeddings (LangChain, LlamaIndex, etc.).
High level of English proficiency required to interact with a globally-based development team and client stakeholders.
Deep expertise in Python for backend services and AI integration (replacing traditional Java/C# requirements).
Demonstrated, hands-on experience utilizing Azure AI Foundry to build, deploy, and manage AI models and agents.
Proven track record of building and managing complex API integrations for data ingestion, extraction, and classification.
Strong understanding of security engineering, specifically implementing PII redaction, anonymization pipelines, and secure data handling in AI workflows.
Experience delivering well-tested, scalable, secure, and performant enterprise-level systems that achieve client business outcomes.
Strong track record of working within Agile software development frameworks.
Proficiency with AI-assisted development tools (Claude Code, Cursor, GitHub Copilot) as a core daily practice, including pipeline construction, test generation, and documentation.

Additional Experience Desired

Strong programming skills in Python, and familiarity with libraries such as PyTorch, TensorFlow, and Scikit-Learn.
Exposure to Matplotlib, Seaborn, or Plotly
Familiarity with building and operating Cloud Native applications, including infrastructure-as-code and observability practices.
Experience with at least one cloud platform and CI/CD for ML (GitHub Actions, MLflow, etc.).
Familiarity with emerging AI Regulations (e.g., EU AI Act, NIST AI RMF) and practical implementation of AI safety guardrails.

Benefits

Medical Insurance benefits as per company policy.
Life Insurance as per company policy
15 days of paid vacation plus additional days based on tenure
Vacation bonus as per local law
Sick leave and paid holidays as per local law
Profit sharing as per local law
Paternity and maternity leave as per as per local law
Marriage, bereavement and graduation leaves as per company policy
Christmas bonuses as per local law
Work from home allowance as per company policy
Punctuality and attendance bonuses as per company policy
Food tickets as per company policy
Direct deposit of payroll.
Paid professional certifications

What It's Like to Work at 3Pillar

At 3Pillar, we create an environment where people can do their best work while maintaining a healthy work-life balance.

Flexibility & Well-being – Our remote-first approach gives you the flexibility to work where you perform best, while prioritizing your well-being and personal commitments.
Global Community – Collaborate with talented colleagues across the globe in a culture built on connection, support, and shared success.
Your Voice Matters – We foster open communication and multiple feedback channels, ensuring every employee has the opportunity to be heard and make an impact.
Growth & Development – Gain exposure to diverse clients, industries, and challenges that accelerate learning and career growth.

Our culture is guided by four core values: Collaboration, Outperform, Respect, and Evolve—the principles that shape how we work, grow, and succeed together.

We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses and identifying potential inconsistencies or verification signals in application materials based on available information. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.

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full stack software engineer, observability empleos en desde casa

Lead AI Integration Engineer

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