Top Tech Jobs & Startup Jobs

Lead end-to-end data migrations for LegalTech SaaS implementations. Analyze legacy financial and practice-management systems, design mappings and ETL strategies, extract and transform data using SQL and Python, execute test and production migrations, validate results, reconcile financial datasets, resolve data-quality issues, and document technical specifications. Collaborate with project managers, consultants, client IT teams, and non-technical stakeholders while improving automation, templates, and migration best practices.

Lead the development, optimization, and deployment of AI solutions using AWS services, machine learning frameworks, generative AI, RAG, vector databases, and prompt engineering. Guide AI engineers, integrate AI capabilities into products, improve model reliability, and collaborate with technical and non-technical stakeholders.

Develop, optimize, and deploy AI and machine learning solutions using AWS services, foundation models, RAG, vector databases, and agentic AI frameworks. Lead AI engineers, improve model reliability and performance, integrate AI capabilities into products, and collaborate with technical and non-technical stakeholders. The role also involves prompt engineering, data processing, model evaluation, and adopting emerging AI technologies.

Lead end-to-end data migration and ETL processes for LegalTech SaaS implementations. Analyze legacy financial and practice-management data, map schemas, extract and transform data using SQL and Python, execute dry runs and production loads, validate accuracy, reconcile results, resolve data-quality issues, and document migration specifications. Collaborate with project managers, implementation consultants, client IT teams, and non-technical stakeholders while improving migration automation and best practices.

Lead the development, optimization, and deployment of AI solutions using AWS services, generative AI, RAG, vector databases, and machine learning frameworks. Fine-tune models, improve reliability, reduce hallucinations, and integrate AI capabilities into products. Lead AI engineers, manage projects, collaborate with stakeholders, and evaluate emerging technologies. The role also involves prompt engineering, data preprocessing, feature engineering, and scalable model deployment.

Designs and implements AWS cloud architectures integrating modernization, data engineering, generative AI, and machine learning. Leads client architecture sessions, presales engagements, cloud migrations, data pipeline and lakehouse development, governance, security, and multi-region deployments. Advises clients on scalable, secure, cost-optimized solutions while collaborating with sales and delivery teams. Requires extensive AWS experience, AI/ML and data architecture expertise, infrastructure-as-code proficiency, and strong customer-facing skills.

Designs and implements scalable AWS cloud architectures focused on modernization, data engineering, generative AI, and machine learning. Leads client architecture sessions, presales engagements, cloud migrations, governance initiatives, and multi-region deployments. Develops AI/ML solutions using AWS services, designs data pipelines and lakes, modernizes legacy applications with containers and serverless technologies, and advises clients on security, compliance, cost optimization, and Well-Architected practices.

Designs, implements, and optimizes enterprise Amazon Connect contact center solutions using AWS serverless services, conversational AI, REST APIs, and enterprise integrations. Configures contact flows, routing, queues, analytics, recording, and agent workspaces; troubleshoots deployments for scalability, reliability, and security. Collaborates with customers and technical teams on requirements, architecture, workshops, demonstrations, proof-of-concepts, proposals, and go-to-market initiatives.

Designs, deploys, and maintains resilient AWS cloud infrastructure and production Kubernetes environments. Builds infrastructure as code and CI/CD workflows, manages containerization, monitoring, logging, networking, security, and operational automation. Works directly with customers and stakeholders, improves operational procedures, troubleshoots infrastructure issues, and mentors junior DevOps engineers. The role requires strong AWS architecture, Kubernetes, Terraform or CloudFormation, CI/CD, Docker, scripting, configuration management, and cloud-native security expertise.

Build, deploy, and maintain resilient AWS cloud infrastructure and production Kubernetes environments. Develop infrastructure as code, CI/CD workflows, automation, monitoring, and security practices. Troubleshoot infrastructure issues, gather customer requirements, improve operational procedures, and manage cloud-native deployments. The role also involves independently delivering customer projects and mentoring junior DevOps engineers.