AI Engineer (III)

BravoTECH; Richardson (TX); Hybrid; USD 140,000 - 210,000; Full time

Benefits offered by this job

Health, dental, and vision insurance

Retirement savings plan with company 1

Paid time off and holidays

Professional development opportunities

Job summary

BravoTECH is seeking an AI Engineer to design, build, and scale advanced AI applications in the PropTech space. You will work with state-of-the-art foundation models, RAG systems, and multi-agent orchestration to deliver production-grade AI solutions.

The role requires 2–3 days in-office in Richardson, TX, collaborating with product, design, and engineering teams. You will own end-to-end AI features—from ideation to deployment—across data pipelines, models, and integrations, with a strong

Qualifications

• 5+ years in software engineering and/or data science with 2+ years in Generative AI/LLMs.
• Degree or equivalent practical experience in CS/ML/Data Science.
• Strong Python for AI/ML, data pipelines, and backend services.
• Proficiency in JavaScript/TypeScript for frontend and/or Node backend.
• Experience with SQL and relational data modeling.
• Hands-on with OpenAI/Google/Hugging Face APIs and LLMs.
• Familiarity with LangChain, OpenAI Agents SDK, and vector databases.
• Docker, Kubernetes, and cloud platforms (GCP/AWS/Azure).
• Excellent communication with technical and non-technical stakeholders.

Responsibilities

• Evaluate and use LLMs and multimodal models from multiple providers for chat assistants and copilots.
• Design agentic workflows with tool-calling and multi-agent orchestration.
• Develop and optimize prompts, guardrails, and structured outputs (JSON).
• Architect and implement RAG pipelines with vector stores and data ingestion.
• Build frontend experiences and backend services to orchestrate AI calls.
• Monitor performance, latency, cost, and reliability of AI features.

Skills

Python for AI/ML

Data pipelines

Back-end services

JavaScript/TypeScript

SQL

CI/CD

Git workflows

Communication

Education

Bachelor's degree in CS or related field

Equivalent practical experience

Tools

OpenAI Agents SDK

LangChain

Google ADK

Kubernetes

Docker

EKS/GKE/AKS

Cursor

Windsurf

Job description

AI Engineer

Company is at the forefront of the Generative AI revolution, dedicated to shaping the future of artificial intelligence. Our Agentic AI team is focused on driving innovation by building next generation AI applications and enhancing existing systems with Generative AI capabilities. We are seeking an AI Engineer to help us with the development, deployment, and scaling of advanced AI applications that address real-world challenges. In this role, you will focus on designing, building, and scaling advanced AI applications in the PropTech space. You will work with state-of-the‑art foundation models, RAG architectures, and multi‑agent systems while partnering closely with product, design, and engineering teams. You will be responsible for taking AI concepts from ideation to production, owning end‑to‑end solutions that improve our products and transform user experiences. In this role you would be expected to come into the office 2-3 days a week (Tues & Wed are in office days).

Responsibilities

Agentic AI & Generative Application Engineering Evaluate and use LLMs and multimodal models from multiple providers (e.g., OpenAI, Google, Anthropic, etc.) for: Conversational assistants, task‑based copilots, and AI agents Summarization, content generation, document understanding, generative analytics Basic multimodal use cases (text + image, text + document, and soon video/audio) Design and implement agentic workflows (e.g., tool‑calling, multi‑step reasoning, multi‑agent orchestration) using: LangChain, OpenAI Agents SDK, Google ADK or similar frameworks. Prompt Engineering & Guardrails Design and optimize prompts and system instructions to: Improve task completion, reliability, and latency Minimize hallucinations and toxic/unsafe outputs Implement structured outputs (JSON/JSON Schema) Develop function/tool calling and prompts that help AI call them properly Integrate safety/guardrail layers (e.g., content moderation APIs, Guardrails AI, Rebuff, custom policies) to keep conversations focused RAG & Knowledge Integration Architect and implement RAG pipelines: Choose and configure vector databases (e.g., PGVector, Vertex AI Search, Pinecone, etc.) Build ingestion pipelines for internal data (documents, tickets, logs, property data, etc.) Implement knowledge retrieval process that draws from multiple sources and uses reranking to improve the response quality. Explore emerging retrieval techniques (semantic caching, knowledge graphs, long‑context models, memory systems). Full‑Stack & System Integration Build or integrate front‑end experiences (React / Vue / Svelte / Web RTC) for AI agents and copilots. Develop back‑end services to orchestrate AI calls using REST, gRPC, WebSockets, or MCP; ensure scalability and observability. Integrate with internal systems and PropTech data sources using secure APIs and data contracts. Evaluation, Monitoring & Optimization Design and maintain evaluation pipelines and benchmarks for LLM‑based features: Offline metrics (accuracy, relevance, latency, cost) Human‑in‑the‑loop evaluations where needed Use AI observability and tracing tools (e.g., LangSmith, OpenTelemetry, etc.) to monitor quality. Optimize for performance, reliability, latency, and cost through: Model selection and routing (e.g., small vs. large models, Google vs. OpenAI) Prompt/token optimization and caching strategies. Collaboration, Documentation & Delivery Collaborate with cross‑functional teams (Product, Design, Domain Experts, Data Science, Platform Engineering) to define requirements and success metrics. Participate in architecture and design reviews; write clear technical documentation and runbooks. Contribute to shared libraries, templates, and best practices for AI development. Work in an Agile environment and own features from design through deployment and maintenance.

Qualifications

5+ years of total experience in Software Engineering and/or Data Science, with at least2 years focused on Generative AI/LLMs. Degree in Computer Science, Machine Learning, Data Science, or related field, or equivalent practical experience. Strong proficiency in: Pythonfor AI/ML, data pipelines, and back‑end services JavaScript/TypeScriptfor front‑end and/or Node services SQLand experience working with relational databases and basic data modeling Working with coding assistants like Windsurf, Cursor, Codex, etc. Proven experience building production‑grade software: Writing clean, testable, maintainable code Using CI/CD pipelines, code reviews, and Git workflows Hands‑on experience with: At least one agentic/orchestration framework (OpenAI Agents SDK, Google ADK, LangChain, etc.) LLM APIs and/or open‑source models (e.g., via OpenAI, Google, Hugging Face, Ollama) Vector embeddings, vector databases, and RAG architectures Experience with one or more major cloud platforms (GCP, Azure, and AWS) and: Docker for containerization Kubernetes or a managed container service (e.g., EKS, GKE, AKS) Strong communication skills and ability to collaborate with both technical and non‑technical stakeholders.

Nice‑to‑Have Skills / Abilities

Experience with: Voice‑enabled AI agents (STT, TTS, WebRTC, Twilio Voice, Socket.IO, VAPI) Multimodal models (e.g., GPT models including Realtime, Gemini Pro Vision, etc.) Orchestrating multiple models (routing, ensembles, fallback strategies) Familiarity with: AI experiment tracking and evaluation frameworks (e.g., OpenAI Evals, Langsmith Evals, etc.) Feature stores, data versioning (e.g., Feast, DVC), and MLOps workflows Browser automation software such as PlayWright Background in: AI security, privacy, and compliance (PII handling, SOC2, GDPR considerations) A/B testing and online experimentation for AI features.

Salary and Benefits

Competitive salary package along with a comprehensive benefit plan that includes:

• Health, dental, and vision insurance.


• Retirement savings plan with company match.


• Paid time off and holidays.


• Professional development opportunities.