BigStep Technologies - Technical Lead - Artificial Intelligence Workflows

We are seeking an experienced AI Workflow Automation Tech Lead to design, architect, and lead intelligent automation solutions that combine AI/ML, workflow orchestration, and enterprise systems integration. This is a hands-on leadership role where you will guide teams in building scalable, resilient, and explainable AI-driven workflows that automate complex business processes end-to-end.

You will work closely with product owners, data scientists, platform engineers, and business stakeholders to translate requirements into production-grade AI automation solutions.

Key Responsibilities :

Architecture & Solution Design :

- Design and own end-to-end AI-driven workflow architectures integrating ML models, LLMs, rule engines, APIs, and enterprise systems.

- Define workflow orchestration strategies using tools such as Temporal, Airflow, Camunda, Step Functions, or similar.

- Architect scalable, event-driven and microservices-based automation platforms.

- Ensure solutions follow security, compliance, observability, and reliability best practices.

Technical Leadership :

- Act as Tech Lead for AI automation initiatives, guiding engineers across design, development, and deployment.

- Establish coding standards, architectural guidelines, and best practices.

- Review solution designs, code, and AI pipelines for performance, scalability, and maintainability.

- Mentor engineers and enable knowledge sharing across teams. AI & Intelligent Automation

- Integrate AI/ML models and LLMs into automated workflows (classification, extraction, decisioning, summarization, recommendations).

- Design human-in-the-loop workflows for exception handling and AI confidence thresholds.

- Implement model lifecycle management, versioning, and monitoring within workflows.

- Ensure explainability, traceability, and auditability of AI-driven decisions. Workflow

Development & Integration :

- Develop and orchestrate workflows that integrate with enterprise applications, data platforms, and third-party APIs.

- Implement API-first and event-driven integration patterns.

- Automate business processes across domains such as operations, finance, supply chain, customer support, or HR.

Cloud, DevOps & Platform Engineering :

- Architect and deploy solutions on AWS / Azure / GCP using cloud-native services.

- Implement CI/CD pipelines for workflow code, AI models, and infrastructure.

- Enable observability using logging, metrics, tracing, and alerting tools.

- Optimize cost, performance, and reliability of AI automation platforms.

Agile Delivery & Stakeholder :

- Collaboration Partner with Product Managers, Business Analysts, and Stakeholders to refine requirements and define success metrics.

- Drive Agile ceremonies, sprint planning, and technical backlog prioritization.

- Translate business processes into automation roadmaps and execution plans.

Required Technical Skills :

Core Programming & Platforms :

- Strong hands-on experience with Python (preferred) and/or Java / Node.js.

- Experience building microservices and distributed systems.

Workflow & Automation Technologies :

- Hands-on experience with workflow engines such as Airflow, Temporal, Camunda, Step Functions, Prefect, or similar.

- Experience with RPA / IPA platforms (UiPath, Automation Anywhere, Power Automate) is a plus. AI / ML / LLM Practical experience integrating ML models and LLMs (OpenAI, Azure OpenAI, Bedrock, Vertex AI, etc.).

- Understanding of prompt engineering, model orchestration, and AI evaluation techniques.

- Familiarity with ML pipelines, feature stores, and model monitoring.

Data & Integration :

- Strong understanding of REST / GraphQL APIs, messaging systems (Kafka, SQS, Pub/Sub), and event-driven design.

- Experience with SQL and NoSQL databases.

Cloud & DevOps :

- Hands-on cloud experience with AWS / Azure / GCP. Experience with Docker, Kubernetes, and IaC tools (Terraform, CloudFormation).

- Strong CI/CD experience using GitHub Actions, GitLab CI, Jenkins, or similar.

Architecture & Design :

- Strong knowledge of distributed system design, resiliency patterns, and scalability.

- Experience applying SOLID principles, clean architecture, and DDD concepts.

Soft Skills & Leadership:

- Strong stakeholder management and communication skills.

- Ability to translate complex AI concepts into business-friendly explanations.

- Mentoring mindset with a passion for building high-performing teams.

- Strong problem-solving and decision-making abilities.