Jobs at Aptus Data Labs

Lead backend development of scalable Python and Django systems, REST APIs, and microservices. Integrate AI/ML models into production applications, optimize databases and caching, and ensure security, reliability, and scalability. Collaborate with frontend, AI, data, and DevOps teams; participate in testing, code reviews, deployments, and CI/CD automation. The role requires experience with PostgreSQL, MySQL, MongoDB, Docker, cloud platforms, Celery, Redis, authentication, SSO, and RBAC.

Lead end-to-end Reltio MDM implementations, including data modeling, survivorship, match/merge logic, workflows, integrations, and data pipelines. Configure Reltio and integrate it with enterprise systems using APIs, ETL tools, and middleware. Support data governance, quality, performance optimization, production deployments, incident resolution, documentation, and ongoing enhancements while collaborating with technical and business stakeholders.

Create graphic assets for digital and print media, including websites, social media, advertisements, brochures, and presentations. Design user interfaces for web and mobile applications through research, wireframing, prototyping, and testing. Collaborate with marketing, product, and development teams; maintain design systems and brand consistency; improve usability and accessibility; edit images and videos; and manage multiple projects and deadlines.

Lead end-to-end development and deployment of machine learning, deep learning, NLP, and generative AI solutions. Apply architectures such as CNNs, RNNs, and Transformers; build NLP and RAG applications; optimize model scalability, latency, accuracy, and explainability; collaborate with stakeholders; and mentor junior data scientists while guiding technical delivery.

Design, develop, deploy, and optimize AI and machine learning models for production applications. Train models on large datasets, build deep learning architectures, integrate models into scalable software products, and apply MLOps practices for versioning, deployment, and monitoring. Collaborate with data scientists, engineers, and product managers while deploying AI solutions on cloud platforms. Apply responsible AI practices and stay current with emerging research, tools, and techniques.

Lead the design, implementation, and management of secure AWS infrastructure, service enablement, Infrastructure as Code, and CI/CD pipelines. Establish cloud governance, security, monitoring, backup, disaster recovery, and cost-optimization practices. Collaborate with security and application teams on DevSecOps, support AWS service integration, and mentor junior DevOps engineers.

Design and implement scalable data architectures, models, warehouses, lakes, governance frameworks, and data integration pipelines. Optimize storage and retrieval for performance, cost, quality, and integrity across cloud and on-premise environments. Collaborate with engineers, data scientists, and business teams to support analytics, AI/ML, and real-time processing. Evaluate data technologies and enforce security, privacy, compliance, validation, monitoring, and error-handling practices.

Design and build scalable AWS data lakes, lakehouses, and ETL/ELT pipelines using Glue, Python, and Spark. Integrate structured and semi-structured data from APIs, on-premises systems, and third-party sources. Manage IAM, security controls, governance, and compliance readiness. Automate infrastructure deployments with CI/CD and Docker, operate workloads on ECS or EKS, and monitor pipelines with CloudWatch. Collaborate with platform, AI, analytics, data science, and business teams to deliver reliable data assets.

Designs, develops, deploys, and maintains AI and machine learning models, including generative AI and NLP solutions. Leads AI strategy, researches algorithms, analyzes complex datasets, collaborates with cross-functional teams, and presents technical solutions to varied stakeholders. The role also provides technical guidance, supports project delivery, improves model performance, and uses cloud platforms and CI/CD practices for model operations.

Design, develop, deploy, and maintain application integrations using Dell Boomi AtomSphere. Connect cloud and on-premise systems, build custom connectors and API-led integrations, manage Atoms, Molecules, and APIs, and troubleshoot integration issues. Translate business requirements into scalable solutions while applying integration patterns, ETL, REST/SOAP web services, data protocols, error handling, logging, retries, and data transformation. Collaborate with cross-functional teams and support integration lifecycle management.

Design, develop, and deploy AI-driven full-stack applications. Integrate and optimize AI/ML models, build responsive front ends and scalable back-end APIs, manage databases and cloud services, and deploy applications using Docker, Kubernetes, and CI/CD pipelines. Collaborate with data scientists, designers, and product teams while applying LLM, NLP, MLOps, and blockchain knowledge.

Design, optimize, and support scalable batch and streaming data pipelines using Databricks, Spark, Delta Lake, Kafka, and SQL. Architect governed data lakes with Unity Catalog, implement data quality and access controls, and automate deployments using CI/CD, DevOps, and infrastructure-as-code tools. Collaborate on Generative AI and LLM data pipelines, troubleshoot production issues, and contribute to data platform architecture and scalability.

Aptus Data Labs is hiring for multiple openings spanning cloud infrastructure, data engineering, data architecture, master data management, application integration, AI, full-stack and frontend development, UX/UI, and executive leadership. The company seeks collaborative, adaptable professionals interested in deep technology, artificial intelligence, and impactful real-world projects.

Own global enterprise revenue growth across AI, data engineering, digital transformation, and product offerings. Lead full-cycle B2B sales, strategic GTM execution, CXO engagement, pipeline forecasting, solution shaping, proposals, negotiations, and deal closure. Develop market expansion strategies, pricing models, sales playbooks, and partnerships with hyperscalers and AI/ML ecosystem providers. Represent the company at executive workshops, industry events, and global summits while driving new client acquisition and account expansion.

Lead enterprise data architecture and modernization across global teams. Design and operationalize Databricks Lakehouse platforms on AWS, including ingestion, governance, orchestration, security, and consumption. Implement Medallion architecture across more than 100 sources using Boomi and Databricks pipelines. Own Reltio MDM, metadata, data quality, lineage, cataloging, AI-ready datasets, and enterprise standards. Mentor data engineering and platform teams while partnering with stakeholders on cloud migration, compliance, observability, and cost optimization.

Leads the architecture, development, deployment, and governance of AI, machine learning, and Generative AI solutions. Designs scalable LLM systems using embeddings, vector databases, RAG, fine-tuning, prompt engineering, evaluations, and agentic workflows. Defines AI roadmaps, guides solutions from proof of concept to production, establishes responsible AI and security standards, troubleshoots production performance, collaborates with cross-functional stakeholders, and mentors engineers.

Generate qualified B2B leads for IT, analytics, and AI SaaS offerings by researching prospects, building targeted lists, and conducting cold outreach through email, LinkedIn, and WhatsApp. Qualify inbound leads, schedule sales meetings and demos, maintain CRM records, collaborate on campaigns, personalize outreach using industry research, and report on lead metrics and conversion performance.

Lead AI strategy and roadmap execution while mentoring AI engineers and data scientists. Architect scalable production AI pipelines, optimize inference across cloud and edge environments, and implement MLOps, monitoring, drift detection, retraining, and governance practices. Design and deploy machine learning, deep learning, NLP, generative AI, RAG, and agentic solutions. Collaborate with business and technical stakeholders, evaluate AI opportunities, build investment cases, track ROI, and communicate technical solutions.

Designs end-to-end Databricks Lakehouse architectures, leads enterprise data pipelines, ETL frameworks, and real-time streaming applications. Defines architecture standards, mentors engineering teams, translates business needs into scalable solutions, and implements CI/CD, orchestration, security, and cloud infrastructure practices. Optimizes large-scale data systems for performance and cost while overseeing integrations with Power BI, Kafka, Snowflake, and upstream and downstream platforms.