BrickRed Systems
We are looking for a
hands‑on Tech Lead
who can drive the design and development of cloud‑native systems
built for AI‑first automation, decision intelligence, and agentic workflows . In this role, you will own the technical direction for AI adoption, mentor engineers on modern AI frameworks, and architect scalable, secure backend systems across Azure.
You will work closely with engineering, data science, and product teams to embed intelligent automation into enterprise platforms—while remaining an active contributor in coding, experimentation, and architectural design.
If you are someone who thrives at the intersection of
cloud engineering, distributed systems, and applied AI , this role is for you.
What You’ll Lead & Deliver AI Adoption & Technical Leadership
Own the organization’s
AI adoption roadmap , including architecture, model integration strategy, and evaluation of emerging frameworks.
Guide engineers on best practices for
LLMs, RAG pipelines, embeddings, vector search, Snowflake/Snowpark ML, and real-time AI inference .
Evaluate and integrate frameworks such as
LangChain, Semantic Kernel, AutoGen, Azure Cognitive Services , and open‑source agentic toolkits.
Drive hands‑on POCs for intelligent automation, LLM‑enabled workflows, AI copilots, and data‑quality agents.
Design, build, and optimize
APIs, Azure Functions, serverless orchestration, and event‑driven systems
to power scalable AI‑ready platforms.
Write clean, maintainable, and testable code in
C#, Python, or TypeScript
across backend services.
Architect and implement microservices, Durable Functions, and Azure Event Grid–based eventing patterns.
Build distributed, reliable, and secure cloud systems with strong emphasis on latency, resilience, and observability.
Integrate with SQL, NoSQL, and cloud‑native data stores while designing efficient and scalable data access layers.
Collaborate with data engineering and ML teams to support
feature pipelines, data ingestion, Snowflake integration, and AI model serving .
Contribute to ML‑powered monitoring, automated data quality checks, and intelligent ETL optimization.
Engineering Excellence & Mentorship
Lead code reviews, technical design sessions, and architecture discussions.
Establish engineering best practices—including automated testing, CI/CD, IaC, Cloud cost optimization, and observability.
Mentor engineering teams on distributed systems, AI techniques, and responsible AI usage.
Qualifications Required
8–12+ years
of professional software engineering experience (backend or full‑stack), with at least
3+ years
in technical leadership or senior tech lead capacity.
Deep hands‑on expertise in
C# or Python , solid grounding in OOP and functional programming concepts.
Strong experience architecting and deploying:
REST/gRPC APIs
Event‑driven systems (Event Grid, Service Bus, Durable Functions)
Microservices in cloud‑native environments
Strong understanding of
distributed systems , serverless patterns, and cloud security.
Experience integrating with various data stores: SQL, NoSQL, or cloud‑native systems.
Strong communication skills with the ability to translate complex requirements into maintainable technical solutions.
AI & ML Skills (Required Next‑Gen Skills)
Practical experience with:
Vector embeddings & vector stores
Hands‑on experience building
agentic workflows , automated decision systems, or LLM‑connected services.
Ability to guide teams on model selection, evaluation, integration, and MLOps‑lite patterns.
Bonus / Preferred
Experience with Snowflake, Snowpark ML, Databricks, or Azure ML.
Familiarity with ONNX, model optimization, or API‑based model hosting.
Prior experience developing intelligent automation or enterprise AI copilots.
About Brickred Systems Brickred Systems is a global leader in next‑generation technology, consulting, and business process service companies. We enable clients to navigate their digital transformation. Brickred Systems delivers a range of consulting services to our clients across multiple industries around the world. Our practices employ highly skilled and experienced individuals with a client‑centric passion for innovation and delivery excellence.
With ISO 27001 and ISO 9001 certification and over a decade of experience in managing the systems and workings of global enterprises, we harness the power of cognitive computing hyper‑automation, robotics, cloud, analytics, and emerging technologies to help our clients adapt to the digital world and make them successful. Our always‑on learning agenda drives their continuous improvement through building and transferring digital skills, expertise, and ideas from our innovation ecosystem.
Senioriy level Mid‑Senior level
Employment type Contract
Job function Information Technology
Industries IT Services and IT Consulting
#J-18808-Ljbffr
hands‑on Tech Lead
who can drive the design and development of cloud‑native systems
built for AI‑first automation, decision intelligence, and agentic workflows . In this role, you will own the technical direction for AI adoption, mentor engineers on modern AI frameworks, and architect scalable, secure backend systems across Azure.
You will work closely with engineering, data science, and product teams to embed intelligent automation into enterprise platforms—while remaining an active contributor in coding, experimentation, and architectural design.
If you are someone who thrives at the intersection of
cloud engineering, distributed systems, and applied AI , this role is for you.
What You’ll Lead & Deliver AI Adoption & Technical Leadership
Own the organization’s
AI adoption roadmap , including architecture, model integration strategy, and evaluation of emerging frameworks.
Guide engineers on best practices for
LLMs, RAG pipelines, embeddings, vector search, Snowflake/Snowpark ML, and real-time AI inference .
Evaluate and integrate frameworks such as
LangChain, Semantic Kernel, AutoGen, Azure Cognitive Services , and open‑source agentic toolkits.
Drive hands‑on POCs for intelligent automation, LLM‑enabled workflows, AI copilots, and data‑quality agents.
Design, build, and optimize
APIs, Azure Functions, serverless orchestration, and event‑driven systems
to power scalable AI‑ready platforms.
Write clean, maintainable, and testable code in
C#, Python, or TypeScript
across backend services.
Architect and implement microservices, Durable Functions, and Azure Event Grid–based eventing patterns.
Build distributed, reliable, and secure cloud systems with strong emphasis on latency, resilience, and observability.
Integrate with SQL, NoSQL, and cloud‑native data stores while designing efficient and scalable data access layers.
Collaborate with data engineering and ML teams to support
feature pipelines, data ingestion, Snowflake integration, and AI model serving .
Contribute to ML‑powered monitoring, automated data quality checks, and intelligent ETL optimization.
Engineering Excellence & Mentorship
Lead code reviews, technical design sessions, and architecture discussions.
Establish engineering best practices—including automated testing, CI/CD, IaC, Cloud cost optimization, and observability.
Mentor engineering teams on distributed systems, AI techniques, and responsible AI usage.
Qualifications Required
8–12+ years
of professional software engineering experience (backend or full‑stack), with at least
3+ years
in technical leadership or senior tech lead capacity.
Deep hands‑on expertise in
C# or Python , solid grounding in OOP and functional programming concepts.
Strong experience architecting and deploying:
REST/gRPC APIs
Event‑driven systems (Event Grid, Service Bus, Durable Functions)
Microservices in cloud‑native environments
Strong understanding of
distributed systems , serverless patterns, and cloud security.
Experience integrating with various data stores: SQL, NoSQL, or cloud‑native systems.
Strong communication skills with the ability to translate complex requirements into maintainable technical solutions.
AI & ML Skills (Required Next‑Gen Skills)
Practical experience with:
Vector embeddings & vector stores
Hands‑on experience building
agentic workflows , automated decision systems, or LLM‑connected services.
Ability to guide teams on model selection, evaluation, integration, and MLOps‑lite patterns.
Bonus / Preferred
Experience with Snowflake, Snowpark ML, Databricks, or Azure ML.
Familiarity with ONNX, model optimization, or API‑based model hosting.
Prior experience developing intelligent automation or enterprise AI copilots.
About Brickred Systems Brickred Systems is a global leader in next‑generation technology, consulting, and business process service companies. We enable clients to navigate their digital transformation. Brickred Systems delivers a range of consulting services to our clients across multiple industries around the world. Our practices employ highly skilled and experienced individuals with a client‑centric passion for innovation and delivery excellence.
With ISO 27001 and ISO 9001 certification and over a decade of experience in managing the systems and workings of global enterprises, we harness the power of cognitive computing hyper‑automation, robotics, cloud, analytics, and emerging technologies to help our clients adapt to the digital world and make them successful. Our always‑on learning agenda drives their continuous improvement through building and transferring digital skills, expertise, and ideas from our innovation ecosystem.
Senioriy level Mid‑Senior level
Employment type Contract
Job function Information Technology
Industries IT Services and IT Consulting
#J-18808-Ljbffr