Backend Software Engineer (Applied AI)

Location

Remote from LATAM

Contract Type

Full-time Contractor

Time Zone Alignment

CT

About In All Media

We are a Managed Nearshore Teams provider headquartered in Austin, specializing in building and embedding high-performing software development teams. From design to deployment, we deliver customized solutions by connecting global talent with innovative client projects. Our model allows you to work on international challenges, collaborate with diverse teams, and grow your career while being part of a company that values expertise, creativity, and impact.

Project Overview

In this role, you will be at the forefront of the AI revolution, supporting a high-impact project focused on integrating LLM capabilities into production enterprise systems. You will join a collaborative, fast-paced team dedicated to building the next generation of AI-powered software. The project involves architecting sophisticated multi-step task orchestration workflows, developing autonomous AI agents, and bridging AI models with external platforms using open integration standards like the Model Context Protocol (MCP). As a Backend Engineer, you will be instrumental in executing rapid prototyping and driving production support to deliver highly reliable, goal-oriented AI systems.

Key Responsibilities

AI Integration

Build AI-powered software and integrate Large Language Model (LLM) capabilities seamlessly into production enterprise systems.

Agentic Development

Design and develop autonomous AI agents, tool-calling systems, and multi-step task orchestration workflows.

MCP Integration

Leverage Model Context Protocol (MCP) or equivalent open integration standards (e.g., custom tool-calling interfaces, JSON-RPC adapters) to connect AI models with external platforms and tools.

Backend Architecture

Build and maintain scalable distributed software architectures, utilizing REST/gRPC APIs and applying strong system design principles.

Context & Reliability Management

Optimize context window management and implement strict reliability patterns for LLM execution at scale.

Agile Delivery

Execute across the full software lifecycle—from experimentation and rapid prototyping to production support—under tight delivery timelines.

Must-Have Skills

Engineering Experience

Hands-on software engineering, backend systems, or applied AI engineering experience. (4+ YEARS OF EXPERIENCE)

Core Programming Mastery

Advanced proficiency in Python and/or Java for backend development and algorithm execution.

Applied AI & LLM Systems

Direct, proven experience building AI-powered software or integrating LLMs into enterprise-grade applications.

Agentic Frameworks

Hands-on experience developing autonomous AI agents and multi-step workflows.

MCP Integration Literacy

Practical experience using Model Context Protocol (MCP), custom tool-calling, or JSON-RPC adapters.

Production Fundamentals

Strong grounding in distributed architectures, API design (REST/gRPC), and reliability patterns.

Mindset & Delivery

Proven ownership mindset, comfortable navigating both rapid experimentation and robust production support.

Fluent English

Excellent verbal and written communication skills for daily technical collaboration and documentation.

Nice-to-Have Skills

Advanced AI Architectures

Hands-on experience with Retrieval-Augmented Generation (RAG), multi-agent orchestration frameworks, semantic search, or vector database platforms (e.g., Pinecone, Qdrant, Milvus).

Enterprise Platform Integrations

Background integrating AI solutions with platforms such as Salesforce, Jira, Slack, or internal developer portals.

AI Observability & MLOps

Familiarity with cloud-native infrastructure (AWS/GCP/Azure), containerization (Docker/Kubernetes), and AI monitoring platforms (e.g., LangSmith, Arize, Datadog).

Safety & Lifecycle Management

Experience implementing model guardrails, safety protocols, evaluation suites, and prompt/version control management.

Time Zone & Collaboration

This role is 100% remote from LATAM and requires consistent overlap with teams in Central Time (CT). Flexibility is expected to accommodate key ceremonies, stand-ups, and collaborative sessions within standard Austin business hours.

Language

All interviews, documentation, and daily communication are in English.

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