Python Developer Internship

About VerbaFlo.ai 

VerbaFlo.ai is a fast-growing AI SaaS startup revolutionizing how businesses leverage AI-powered solutions. As a part of our dynamic team, you’ll work alongside industry leaders and visionaries to drive innovation and execution across multiple functions.

Role Overview 

We are looking for an Engineering Manager to design and develop user-friendly, scalable, and high-performance web applications. This role requires deep expertise in backend technologies, attention to detail, and the ability to collaborate with cross-functional teams.

Job Type: Onsite [Mon - Fri]

Shift Timings: 12 pm to 8 pm IST

Responsibilities 

• Design, develop, and maintain scalable backend systems, APIs, and data pipelines.
• Collaborate closely with frontend engineers, product managers, and AI teams to deliver cohesive features and seamless user experiences.
• Ensure the reliability, security, and performance of backend systems.
• Write clean, maintainable, and efficient code using modern backend practices.
• Implement automated testing, CI/CD workflows, and infrastructure as code (where applicable).
• Own the end-to-end lifecycle of backend features, from architecture to deployment.
• Monitor production systems and resolve performance and scalability issues.
• Contribute to architectural decisions and help evolve our engineering best practices.
• Lead and define backend architecture decisions, ensuring systems are built for long-term scalability and maintainability.
• Mentor and guide junior and mid-level engineers through code reviews, technical discussions, and design feedback.
• Act as a technical anchor for cross-functional initiatives, translating ambiguous product requirements into clear engineering plans.

Requirements 

• 7-11 years of overall experience in backend development [Required]. 
• 1-2+ years of experience working as an Engineering Manager [Required].
• 2-4 years of experience working in a startup [Seed/Series A or B] [Required]
• Proficiency in Node.js, Python, or Go.
• Deep understanding of RESTful API design.
• Strong experience with databases: PostgreSQL, MongoDB, ElasticSearch.
• Exposure to message queues, job schedulers, or event-driven architectures (e.g., SQS, Celery, etc).
• Familiarity with cloud platforms like AWS, GCP, or Azure and containerization tools (Docker, Kubernetes).
• Experience with Git, CI/CD tools, and writing unit/integration tests.
• Strong problem-solving skills and a mindset geared toward performance and security.
• Excellent communication and collaboration abilities.

Why Join Us?

• Work directly with top leadership in a high-impact role.
• Be part of an innovative and fast-growing AI startup.
• Perks & Benefits: gym membership benefit, workation policy, and company-sponsored lunch.
• Opportunity to take ownership of key projects and drive efficiency.
• A collaborative, ambitious, and fast-paced work environment.

If you’re looking for an exciting role that combines strategy, execution, and leadership exposure, we’d love to hear from you!

Data Engineer — AI / BI

Artificial Intelligence & Business Intelligence | Data & Analytics

Who We Are:

Since our inception back in 2006, Navitas has grown to be an industry leader in the digital transformation space, and we’ve served as trusted advisors supporting our client base within the commercial, federal, and state and local markets.

What We Do:

At our very core, we’re a group of problem solvers providing our award-winning technology solutions to drive digital acceleration for our customers! With proven solutions, award-winning technologies, and a team of expert problem solvers, Navitas has consistently empowered customers to use technology as a competitive advantage and deliver cutting-edge transformative solutions.

Position Overview

We are seeking a Databricks Engineer to design, build, and operate a Data & AI platform with a strong foundation in the Medallion Architecture (raw/bronze, curated/silver, and mart/gold layers). This platform will orchestrate complex data workflows and scalable ELT pipelines to integrate data from enterprise systems such as PeopleSoft, D2L, and Salesforce, delivering high-quality, governed data for machine learning, AI/BI, and analytics at scale.

You will play a critical role in engineering the infrastructure and workflows that enable seamless data flow across the enterprise, ensure operational excellence, and provide the backbone for strategic decision-making, predictive modeling, and innovation

Responsibilities:

Data & AI Platform Engineering (Databricks-Centric):

• Design, implement, and optimize end-to-end data pipelines on Databricks, following the Medallion Architecture principles.
• Build robust and scalable ETL/ELT pipelines using Apache Spark and Delta Lake to transform raw (bronze) data into trusted curated (silver) and analytics-ready (gold) data layers.
• Operationalize Databricks Workflows for orchestration, dependency management, and pipeline automation.
• Apply schema evolution and data versioning to support agile data development.

Platform Integration & Data Ingestion:

• Connect and ingest data from enterprise systems such as PeopleSoft, D2L, and Salesforce using APIs, JDBC, or other integration frameworks.
• Implement connectors and ingestion frameworks that accommodate structured, semi-structured, and unstructured data.
• Design standardized data ingestion processes with automated error handling, retries, and alerting.

 Data Quality, Monitoring, and Governance:

• Develop data quality checks, validation rules, and anomaly detection mechanisms to ensure data integrity across all layers.
• Integrate monitoring and observability tools (e.g., Databricks metrics, Grafana) to track ETL performance, latency, and failures.
• Implement Unity Catalog or equivalent tools for centralized metadata management, data lineage, and governance policy enforcement.

Security, Privacy, and Compliance:

• Enforce data security best practices including row-level security, encryption at rest/in transit, and fine-grained access control via Unity Catalog.
• Design and implement data masking, tokenization, and anonymization for compliance with privacy regulations (e.g., GDPR, FERPA).
• Work with security teams to audit and certify compliance controls.

   AI/ML-Ready Data Foundation:

• Enable data scientists by delivering high-quality, feature-rich data sets for model training and inference.
• Support AIOps/MLOps lifecycle workflows using MLflow for experiment tracking, model registry, and deployment within Databricks.
• Collaborate with AI/ML teams to create reusable feature stores and training pipelines.

Cloud Data Architecture and Storage:

• Architect and manage data lakes on Azure Data Lake Storage (ADLS) or Amazon S3, and design ingestion pipelines to feed the bronze layer.
• Build data marts and warehousing solutions using platforms like Databricks.
• Optimize data storage and access patterns for performance and cost-efficiency.

 Documentation & Enablement:

• Maintain technical documentation, architecture diagrams, data dictionaries, and runbooks for all pipelines and components.
• Provide training and enablement sessions to internal stakeholders on the Databricks platform, Medallion Architecture, and data governance practices.
• Conduct code reviews and promote reusable patterns and frameworks across teams.

  Reporting and Accountability:

• Submit a weekly schedule of hours worked and progress reports outlining completed tasks, upcoming plans, and blockers.
• Track deliverables against roadmap milestones and communicate risks or dependencies.

Required Qualifications:

• Hands-on experience with Databricks, Delta Lake, and Apache Spark for large-scale data engineering.
• Deep understanding of ELT pipeline development, orchestration, and monitoring in cloud-native environments.
• Experience implementing Medallion Architecture (Bronze/Silver/Gold) and working with data versioning and schema enforcement in enterprise grade environments.
• Strong proficiency in SQL, Python, or Scala for data transformations and workflow logic.
• Proven experience integrating enterprise platforms (e.g., PeopleSoft, Salesforce, D2L) into centralized data platforms.
• Familiarity with data governance, lineage tracking, and metadata management tools.

Preferred Qualifications:

• Prior UMGC or USM experience preferred.
• Experience with Databricks Unity Catalog for metadata management and access control.
• Experience deploying ML models at scale using MLFlow or similar MLOps tools.
• Familiarity with cloud platforms like Azure or AWS, including storage, security, and networking aspects.
• Knowledge of data warehouse design and star/snowflake schema modeling.

Equal Employer/Veterans/Disabled

Navitas Business Consulting is an affirmative action and equal opportunity employer. If reasonable accommodation is needed to participate in the job application or interview process, to perform essential job functions, and/or to receive other benefits and privileges of employment, please contact Navitas Human Resources.

Navitas is an equal opportunity employer. We provide employment and opportunities for advancement, compensation, training, and growth according to individual merit, without regard to race, color, religion, sex (including pregnancy), national origin, sexual orientation, gender identity or expression, marital status, age, genetic information, disability, veteran-status veteran or military status, or any other characteristic protected under applicable Federal, state, or local law. Our goal is for each staff member to have the opportunity to grow to the limits of their abilities and to achieve personal and organizational objectives. We will support positive programs for equal treatment of all staff and full utilization of all qualified employees at all levels within Navitas.

DocNexus is revolutionizing the global medical affairs & commercial ecosystem with search. We provide a next-generation data platform that simplifies searching through millions of insights, publications, clinical trials, payments, and social media data within seconds to identify healthcare professionals (HCPs), products, manufacturers, and healthcare systems. Leveraging AI-powered Knowledge Graphs, DocNexus assists life science organizations in finding the right key opinion leaders (KOL/DOLs) who play a crucial role in developing and bringing life-saving pharmaceutical products and medical devices to market. Backed by industry leaders such as Techstars, JP Morgan, Mass Challenge, and recognized as one of the Top 200 Most Innovative Startups by TechCrunch Disrupt, we are committed to transforming healthcare insights. We are seeking a skilled and passionate DevOps Engineer to join our dynamic team and contribute to the efficient development, deployment, and maintenance of our platform.

We are looking for a visionary Sr. Full Stack Engineering Lead who is passionate about building and leading our technology department. The ideal candidate will have a solid technical background and experience in leading a team to drive innovation and growth. As Engineering Lead, you will oversee the development and dissemination of technology for external customers, vendors, and other clients to help improve and increase business.

Leadership and Strategy:

• Lead the engineering team and make strategic decisions regarding the technology stack, project management, and resource allocation.
• Establish the company’s technical vision and lead all aspects of technological development.

Development:

• Develop and maintain the front-end and back-end of web applications.
• Ensure the performance, quality, and responsiveness of applications.
• Collaborate with a team to define, design, and ship new features.

Maintenance and Optimization:

• Maintain code integrity and organization.
• Identify and correct bottlenecks and fix bugs.
• Continually work on optimizing the performance of different applications.

Security: Ensure the security of the web applications by integrating security best practices.

• Regularly update the system to protect against vulnerabilities.

Innovation:

• Research and implement new technologies and frameworks that can improve the performance and user experience of the platform.
• Stay informed on emerging technologies and trends that can potentially impact the company's products and services.

Collaboration and Communication:

• Work closely with other departments to understand their needs and translate them into technical solutions.
• Communicate technology strategy to partners, management, investors, and employees.

Project Management:

• Oversee and support project planning, deadlines, and progress.
• Ensure that the technology standards and best practices are maintained across the organization.

Mentoring and Team Building:

• Foster a culture of innovation and excellence within the technology team.
• Mentor and guide the professional and technical development of team members.

Front-End Development:

• HTML/CSS: For structuring and styling the web pages.
• JavaScript/TypeScript: Core scripting language, along with frameworks like Angular, React, or Vue.js for dynamic and responsive user interfaces.

Back-End Development:

• Python: Using frameworks like Django or Flask for server-side logic.
• Node.js: JavaScript runtime environment for building scalable network applications.
• Ruby on Rails: A server-side web application framework written in Ruby.

Database Management:

• SQL Databases: MySQL, PostgreSQL for structured data storage.
• NoSQL Databases: MongoDB, Cassandra for unstructured data or specific use cases.

Server Management:

• Nginx or Apache: For server and reverse proxy functionalities.
• Docker: For containerizing applications and ensuring consistency across multiple development and release cycles.
• Kubernetes: For automating deployment, scaling, and operations of application containers.

DevOps and Continuous Integration/Continuous Deployment (CI/CD):

• Git: For version control.
• Jenkins, Travis CI, or CircleCI: For continuous integration and deployment.
• Ansible, Chef, or Puppet: For configuration management.

Cloud Services:

• AWS: For various cloud services like computing, database storage, content delivery, etc.
• Serverless Frameworks: Such as AWS Lambda or Google Cloud Functions for running code without provisioning or managing servers.

Security:

• OAuth, JWT: For secure authentication mechanisms.
• SSL/TLS: For secure data transmission.
• Various Encryption Techniques: To safeguard sensitive data.

Performance Monitoring and Testing:

• Selenium, Jest, or Mocha: For automated testing.
• New Relic or Datadog: For performance monitoring.

Data Science and Analytics:

• Python Libraries: NumPy, Pandas, or SciPy for data manipulation and analysis.
• Machine Learning Frameworks: TensorFlow, PyTorch for implementing machine learning models.

Other Technologies:

• GraphQL: For querying and manipulating data efficiently.
• WebSockets: For real-time bi-directional communication between web clients and servers.

• Utilize telephone solicitation, electronic and written correspondence and face-to-face meetings as tools in order to reach and exceed the budgeted sponsorship target for each exhibition/event.
• Research and develop a list of potential sponsors for each exhibition/event.
• Research and develop a list of potential exhibitors when required.
• Develop and maintain relationships with existing and potential sponsorship clients.
• Keep precise records of conversations with all clients, sponsors and exhibitors.
• Update the company database as required.
• Invoice sponsors and exhibitors once agreements have been reached.
• Assist in preparing promotional material to advertise sales opportunities.
• Delegate administrative functions to assistants when possible.
• Experience in International voice process in sales will be an added advantage.