Technical Lead

EXL; Hartford (CT); On-site; USD 140,000 - 180,000; Full time

Job summary

EXL is seeking a Lead Software Engineer / Technical Lead to design, build, and scale cloud-native applications and AI-powered solutions.

The role combines hands-on engineering with technical leadership, driving architecture decisions, mentoring teammates, and delivering enterprise-grade software for business transformation and operational excellence.

Qualifications

• 5+ years of software engineering experience designing and supporting enterprise-scale applications.
• 2+ years in a Technical Lead, Sr Engineer, or equivalent leadership role.
• Strong Python application development and API framework experience (FastAPI/Flask).
• Experience designing microservices, distributed systems, and RESTful APIs.
• Hands-on with GCP and cloud-native application development.

Responsibilities

• Lead design, development, and deployment of scalable, cloud-native applications using Python and modern API frameworks.
• Architect and implement microservices, distributed systems, and RESTful APIs for high-volume workloads.
• Develop on Google Cloud Platform (GCP) with services like GKE, BigQuery, Pub/Sub.
• Design and manage containerized workloads with Docker and Kubernetes (GKE).
• Build and optimize CI/CD pipelines for automated testing and deployment.
• Develop event-driven architectures using Kafka or similar messaging tech.
• Lead Generative AI capabilities, including LLMs, RAG, AI Agents, and agentic workflows.

Skills

Python

GCP

Microservices

Distributed systems

APIs (FastAPI/Flask)

CI/CD

Docker

Kubernetes

GitHub

Kafka

BigQuery

BigTable

Generative AI

LLMs

RAG

Tools

GKE

Docker

Kubernetes

GitHub

CI/CD tooling

Job description

We are seeking a highly skilled Lead Software Engineer / Technical Lead to design, build, and scale cloud-native applications and AI-powered solutions. The ideal candidate will have deep expertise in Python, GCP, microservices architecture, distributed systems, and modern AI technologies including Generative AI, LLMs, RAG, and Agentic AI frameworks. This role combines hands‑on engineering responsibilities with technical leadership, driving architecture decisions, mentoring team members, and delivering innovative enterprise‑grade solutions that support business transformation and operational excellence.

Responsibilities

• Lead the design, development, and deployment of scalable, cloud-native applications using Python and modern API frameworks such as FastAPI and Flask.
• Architect and implement microservices, distributed systems, and RESTful APIs that support high-volume enterprise workloads.
• Develop and maintain applications on Google Cloud Platform (GCP), leveraging services such as GKE, BigQuery, BigTable, Pub/Sub, and other cloud-native technologies.
• Design and manage containerized workloads using Docker and Kubernetes (GKE), ensuring scalability, reliability, and security.
• Build and optimize CI/CD pipelines to enable efficient software delivery, automated testing, and deployment processes.
• Develop event-driven architectures and streaming solutions using Kafka or similar messaging technologies.
• Design and implement robust data processing solutions utilizing SQL, BigQuery, BigTable, and large-scale data platforms.
• Lead the development and operationalization of Generative AI capabilities, including LLM integrations, RAG architectures, AI Agents, and Agentic workflows.

Qualifications

• 5+ years of software engineering experience, including designing and supporting enterprise-scale applications.
• 2+ years of experience serving as a Technical Lead, Sr Engineer, or equivalent technical leadership role.
• Strong expertise in Python application development and modern API frameworks such as FastAPI, Flask, or similar technologies.
• Experience designing and implementing microservices, distributed systems, and RESTful APIs.
• Strong experience with Google Cloud Platform (GCP) and cloud-native application development.
• Hands‑on experience with:
• Docker/Containerization
• CI/CD pipelines and DevOps practices
• GitHub and modern source control practices
• Experience developing and supporting event-driven and streaming solutions using technologies such as Kafka or similar messaging platforms.
• Experience working with cloud-native data technologies including BigQuery, BigTable, SQL, and large-scale data processing solutions.
• Strong understanding of software architecture, design patterns, system reliability, performance optimization, and observability.
• Hands‑on experience implementing and operationalizing:
• Generative AI solutions
• Retrieval-Augmented Generation (RAG)
• AI Agents and Agentic AI workflows
• Prompt engineering and model evaluation frameworks
• Experience integrating enterprise applications with AI platforms such as Gemini, Vertex AI, OpenAI, Claude, or similar technologies.
• Strong analytical, troubleshooting, and production support skills.
• Excellent communication, collaboration, and stakeholder management skills.