Senior Full-Stack Engineer — Cloud & Microservices

TechDigital Group; Redmond (WA); On-site; USD 100,000 - 140,000; Full time

Job summary

An established industry player is seeking a seasoned software engineer with extensive experience in coding and cloud development. This role involves building large-scale applications and utilizing modern technologies like Azure and microservices. The ideal candidate will have a strong background in multiple programming languages and a passion for mentoring less experienced team members. Join a dynamic team where your contributions will drive innovation and success in software solutions, making a significant impact in the tech landscape.

Qualifications

• 8+ years of experience in software engineering and coding in multiple languages.
• Hands-on experience in app development using Azure services.
• Ability to coach and grow less experienced team members.

Responsibilities

• Build large-scale software applications and deliver successful products.
• Utilize cloud development principles, particularly microservices.
• Collaborate with team members to enhance technical skills.

Skills

C

C++

C#

Java

JavaScript

Python

Cloud Development

Microservices

DevOps

Coaching

Education

Bachelor's degree in Computer Science

Master's degree in Computer Science

Tools

ASP.NET

Azure PaaS

GIT

CI/CD

SQL

NoSQL

Job description

Mandatory skill: Expertise in LangChain, LlamaIndex, Semantic Kernel, AutoGen, or equivalent

Key Responsibilities
• Agent Development: Build and orchestrate autonomous AI agents with multi-step reasoning, tool usage, and workflow chaining using frameworks like LangChain, CrewAI, AutoGen, Semantic Kernel, or LlamaIndex.
• LLM Integration & Optimization: Deploy, fine-tune, and serve open-source LLMs (e.g., Llama 3) using Databricks Model Serving; optimize latency, throughput, and cost.
• RAG & Knowledge Systems: Design advanced RAG pipelines leveraging vector search, embeddings, semantic ranking, and enterprise data sources (structured + unstructured).
• Context Engineering: Develop prompt strategies, memory frameworks, and metadata tagging to improve contextual accuracy and response quality.
• UI & Experience Design: Build intuitive AI-driven applications using Databricks Apps (Streamlit/Dash) or modern web frameworks to enable business consumption.
• Data Engineering for AI: Build reliable data pipelines (batch & streaming) supporting training, inference, and feature generation using Delta Lake.
• Security & Governance: Implement enterprise-grade controls using Unity Catalog (row/column-level security, lineage, auditability) aligned with compliance standards.
• LLM Guardrails & Responsible AI: Implement guardrails (e.g., NeMo Guardrails) for prompt injection prevention, hallucination mitigation, and safe output handling.
• MLOps & AIOps: Establish CI/CD pipelines for AI models and agents, including versioning, monitoring, drift detection, observability, and incident response.
• Performance & Cost Optimization: Optimize model performance, GPU/compute usage, and inference cost efficiency across environments.
• Testing & Evaluation
• Collaboration & Stakeholder Engagement
• Documentation & Knowledge Transfer

Required Skills and Qualifications
Databricks & Lakehouse
• Strong experience with Unity Catalog, Delta Lake, Vector Search, Databricks Workflows, and Model Serving
• Hands-on with Lakehouse architecture patterns
LLMs & Generative AI
• Experience with open-source LLMs (Llama, Mistral, etc.), prompting techniques, and fine-tuning approaches
• Strong knowledge of RAG architectures and embedding strategies
AI Engineering & Frameworks
• Expertise in LangChain, LlamaIndex, Semantic Kernel, AutoGen, or equivalent
• Experience building agentic workflows and multi-agent systems
Programming
• Advanced Python proficiency (APIs, web apps, orchestration, data processing)
• Familiarity with REST APIs and microservices architecture
MLOps & Monitoring
• Experience with MLflow, CI/CD pipelines, model lifecycle management, and observability tools
• Knowledge of drift detection and model performance monitoring
Data Engineering Foundations
• Experience with Spark, SQL, and large-scale data processing
• Familiarity with streaming frameworks (Kafka, Structured Streaming)
Security & Governance
• Expertise in AI security risks (prompt injection, jailbreaks, data leakage)
• Experience implementing governance frameworks and compliance controls.