Anika Systems

Title: AI Engineer Location: Remote Job Description: Anika Systems is an outcome-driven technology solutions firm that guides federal agencies in solving complex business challenges and preparing for the future. Our services span AI Strategy, Data Intelligence, AI & Machine Learning, Intelligent Automation, Enterprise Platforms and Engineering, with a specialized focus on National Security and Federal Financial programs. We are dedicated to delivering forward-thinking solutions that accelerate the critical missions of our government clients. Through our VITAL Innovation Lab, we invest heavily in research and development to anticipate mission needs and deliver cutting edge solutions. This position is currently remote; however, in accordance with federal contract requirements and company policy, there may be future changes to work location expectations. Candidates should be prepared for the possibility of a return to the office, either partially or fully, based on client directives, contractual obligations, or company policies. Any such changes will be communicated in advance. Must be a U.S. Citizen with the ability to obtain and maintain a government suitability clearance. The AI Engineers will design and deliver production AI systems across our commercial platform work and our federal modernization programs. This is a hands-on builder role on a small, senior team. Engineers own work end-to-end including data, model integration, services, UI, infrastructure, security, and deployment. You will be expected to make sound technical calls under federal compliance, security, and procurement constraints. Requirements: - Education: Bachelor’s Degree in Computer Science, Computer Engineering, Data Science, Computational Linguistics, or a related field; Master’s is a bonus. - Experience: 1-3 years of professional experience building and shipping ML or NLP systems, including focus on LLM based or Generative AI solutions. - Strong production experience in Python and TypeScript, with modern web frameworks on both sides (e.g. FastAPI, React). - Hands-on integration of LLMs into real applications — streaming, tool / function calling, token accounting, and failure handling — across at least one of OpenAI, Anthropic, Bedrock, Vertex, or Azure OpenAI. - Experience designing agentic systems: multi-step workflows, retrieval-augmented generation, evaluation, and human-in-the-loop guardrails. - Solid relational data modeling on PostgreSQL with an async ORM and migration tooling. - AWS fluency (compute, storage, IAM, secrets, networking, observability) and infrastructure-as-code, ideallyTerraform. - Practical understanding of OAuth / OIDC, JWT, RBAC, multi-tenant isolation, and least-privilege design. - Disciplined testing, linting, and type-checking habits; reviewable diffs and clear written communication. Preferred Skills - Federal program exposure: NIST 800-53, FedRAMP, FISMA, ATO process, or agency-specific data-handling requirements. - Experience with Keycloak or another OIDC provider, RLS-based multi-tenancy, or zero-trust application design. - Working knowledge of a data/lakehouse platform (Databricks, Snowflake) and SQL beyond CRUD. - Document AI / OCR pipelines and modernization of legacy enterprise workflows. - Production observability (CloudWatch, OpenTelemetry, Grafana) and incident-response experience. - Supply-chain hardening: SBOMs, dependency scanning, signed builds, threat modeling.

• Design, develop, and maintain robust ETL/ELT pipelines to ingest, transform, and deliver data across enterprise platforms. • Build scalable data ingestion frameworks for structured and semi-structured data, including XBRL filings and financial datasets. • Implement data transformation logic to support analytics, reporting, and regulatory use cases. • Ensure data pipelines are reliable, performant, and scalable in cloud environments. • Leverage AI-assisted development tools to accelerate pipeline development, testing, and optimization. • Develop and manage data solutions leveraging AWS services (e.g., S3, Airflow, DAGs, Glue, Lambda, Redshift). • Implement and optimize Apache Iceberg table formats for large-scale, ACID-compliant data lakes. • Support lakehouse architectures that unify data lakes and data warehouses. • Optimize data storage and retrieval strategies for performance and cost efficiency. • Enable data platforms that support AI/ML workloads and downstream generative AI use cases. • Design and implement CI/CD pipelines for data pipelines, infrastructure, and analytics code using various tools. • Automate build, test, and deployment processes for ETL pipelines and data platform components. • Implement DataOps best practices, including version control, automated testing, environment promotion, and rollback strategies. • Ensure reproducibility, reliability, and governance of data pipeline deployments across environments. • Integrate AI-driven testing and monitoring tools to improve pipeline quality and reduce operational risk. • Design and implement materialized views and other performance optimization techniques to improve query efficiency. • Develop pipelines to ingest, parse, and normalize XBRL data. • Apply context engineering principles to ensure data is enriched with meaningful metadata, lineage, and business context. • Collaborate with data architects, analysts, and business stakeholders to understand data needs and deliver solutions. • Work in Agile teams to iteratively deliver data capabilities and enhancements.

• Design, develop, and maintain automated QA frameworks for data pipelines, APIs, and analytics platforms using Python and SQL. • Build reusable testing utilities for data validation, regression testing, and pipeline certification. • Integrate automated tests into CI/CD pipelines to support continuous testing and deployment. • Validate ETL/ELT pipelines to ensure accurate ingestion, transformation, and delivery of data. • Develop test strategies for Apache Iceberg-based data lakehouse architectures. • Validate AI-generated metadata, lineage, and transformations for accuracy and traceability. • Collaborate with data and AI teams to test data pipelines supporting RAG, analytics, and machine learning workflows.

• Design and implement scalable enterprise data architectures leveraging AWS and Apache ecosystem technologies (e.g., Spark, Iceberg). • Architect modern AI-enabled data platforms, including support for machine learning, LLM integration, and retrieval-augmented generation (RAG) patterns. • Develop and maintain conceptual, logical, and physical data models, including Entity Relationship Diagrams (ERDs). • Architect modern data lakehouse and data warehouse solutions using Apache Iceberg and cloud-native services. • Define and enforce standards for data integration, data quality, and data lifecycle management. • Design and implement Knowledge Graph architectures, integrating structured and unstructured data sources. • Design and implement Knowledge Graphs and semantic data layers using ontologies, taxonomies, and linked data principles. • Apply GraphRAG architectures to enhance LLM-based applications with context-aware, explainable data retrieval. • Develop and manage ontologies and semantic models to enable interoperability, data discovery, and advanced analytics. • Integrate AI/ML and generative AI capabilities into enterprise data ecosystems, including vector databases and embedding pipelines. • Ensure alignment between data architecture and AI governance, including model transparency, traceability, and responsible AI practices. • Establish and manage enterprise metadata frameworks, including data dictionaries, business glossaries, and technical metadata repositories. • Lead or support stakeholder listening campaigns to gather input from executives, data leaders, and practitioners across the enterprise. • Collaborate with stakeholders to identify data challenges, AI use cases, and opportunities for advanced analytics and automation. • Support analysis of alternatives (AoA) for data and AI tools/platforms, providing recommendations based on cost, capability, and mission fit. • Track and report on data strategy progress, maturity improvements, and program outcomes.

Anika Systems is an outcome-driven technology solutions firm that guides federal agencies in solving complex business challenges and preparing for the future. Our services span AI Strategy, Data Intelligence, AI & Machine Learning, Intelligent Automation, Enterprise Platforms and Engineering, with a specialized focus on National Security and Federal Financial programs. We are dedicated to delivering forward-thinking solutions that accelerate the critical missions of our government clients. This position is 100% remote. Position Summary We are in search of a highly collaborative and experienced Data Analyst to support the Office of Chief Data Officer (OCDO) and the Office of Performance Quality (OPQ) for a federal government contract. In this role, you will design and maintain robust data pipelines, perform in-depth analysis of large-scale datasets, and deliver actionable insights that drive mission decisions. You will work within a Databricks environment leveraging SQL, PySpark, and Python, to transform raw agency data into reliable, governed, and analytics-ready assets. The ideal candidate combines strong engineering fundamentals with analytical acumen and is comfortable operating within complex federal data environments. Candidates must be a U.S. Citizen with the ability to obtain and maintain a government suitability clearance. Key Responsibilities Data Engineering & Pipeline Development - Design, build, and maintain scalable ETL/ELT data pipelines using PySpark and Python within Databricks environments. - Develop and optimize SQL queries, and data models to support analytical and reporting workloads. - Automate data ingestion workflows from disparate agency sources including APIs, flat files, relational databases, and streaming feeds. - Monitor pipeline health, resolve data quality issues, and implement alerting and logging to ensure reliability of data products. - Collaborate with data architects to design and enforce data schemas, partitioning strategies, and performance optimization practices. Data Analysis & Reporting - Conduct exploratory data analysis to identify trends, anomalies, and opportunities for improvement. - Develop self-service analytics dashboards and reports using Databricks SQL, Tableau, or Power BI. - Write complex, performant SQL queries against large datasets to answer ad hoc analytical requests from program managers and leadership. - Translate business questions into clearly scoped analytical tasks and deliver findings as data visualizations, written summaries, or briefings. Collaboration & Stakeholder Support - Work closely with data scientists, program analysts, IT engineers, and agency stakeholders to understand data needs and deliver tailored solutions. - Document pipelines, data models, and analytical notebooks to support knowledge transfer, peer review, and audit readiness. - Participate in Agile sprint ceremonies, contribute to backlog grooming, and deliver iterative data products aligned with program priorities. Required Qualifications - Bachelor's degree in Computer Science, Information Systems, Data Science, Engineering, Mathematics, or a related technical field. - 3+ years of experience in data engineering, data analytics, or a closely related discipline. - Demonstrated experience on federal government programs or supporting a federal agency data environment. - Strong proficiency in SQL — including complex joins, window functions, CTEs, and query performance tuning against large datasets. - Hands-on experience with PySpark for distributed data processing, transformations, and optimization techniques. - Proficiency in Python for scripting, data manipulation, and automation. - Direct experience working within Databricks, including notebooks, jobs, clusters, and Unity Catalog. - Familiarity with data lakehouse concepts including Delta Lake, bronze/silver/gold architecture, and medallion design patterns. - Experience with version control systems (Git/GitHub/GitLab) and collaborative development workflows. Preferred Qualifications - Databricks Certified Associate Developer for Apache Spark or Databricks Certified Data Engineer Associate/Professional. - Experience with cloud platforms such as AWS GovCloud, Microsoft Azure Government, or Google Cloud for Government. - Familiarity with CI/CD practices for data pipelines, including automated testing and deployment using tools like Azure DevOps or GitHub Actions. - Working knowledge of data visualization platforms (Tableau, Power BI) and experience connecting them to Databricks SQL endpoints. - Familiarity with Unity Catalog for data access control, lineage, and governance within Databricks.

Anika Systems is a fast-growing, woman-owned small business that specializes in providing innovative IT solutions for federal government agencies. Our expertise lies in accelerating delivery in Data and Analytics, Intelligent Automation, Application Development, and IT Modernization. We are currently expanding our federal team and are seeking a passionate and talented Data Scientist. This opportunity is 100% remote. Clearance: Must be a U.S. Citizen with the ability to obtain and maintain a government suitability clearance As a Data Scientist at Anika Systems, you will play a pivotal role in enhancing sophisticated dashboards that engage users and emphasize key data points, with a specific focus on specialized reporting for digital assets. This role involves extensive data integration, agile development, and a keen ability to adapt to rapidly changing automation needs and priorities. You will assist in applying industry best practices, creating conceptual business models, and addressing relevant issues to ensure effective solutions. Your expertise will also be crucial in assessing the operational and functional baseline of systems, defining engagement strategies, and meeting organizational needs. Responsibilities and Duties: Data Management: - Cleanse, organize, and translate large volumes of data in various file formats, including digital asset transactions and data supporting tax non-compliance detection. Data Integration: - Manually and automatically load data into SAP IQ and Oracle databases. Data Curation: - Implement data curation strategies to promote data ingestion, integration, quality, and access efficiency. Reporting Enhancement: - Expand reporting methodologies to address data compilation, visualization, and analysis needs for Criminal Investigation and civil business units. Automation: - Automate routine criminal investigative tasks to enhance efficiency and secure data access from systems-of-record and other program information systems. - Integrate with various automation systems, including Robotic Process Automation and client Systems of Record. Document Compilation and Analytics: - Perform criminal investigation case-level document compilation, indexing, searching, and analytics using natural language processing tools.Create dashboard formats incorporating data visualization, analytics, and AI-supported data management and interpretation tools. Big Data Analytics: - Conduct Big Data Analytics studies and analysis, focusing on detecting non-compliance in digital asset transactions. - Perform standard univariate and multivariate statistical analyses, including clustering techniques, multiple regression, and factor analysis. - Apply Artificial Intelligence, incorporating "Trustworthy AI" principles to eliminate bias and unintended consequences. - Develop data visualization and dashboarding solutions. - Promote data science adoption among frontline employees through coaching, feedback, and training. Qualifications: - Bachelor's Degree in a related field or comparable education and experience. - 5 or more years of job-related experience. - Experience with SAS, R, SQL, and Python.

Anika Systems is a fast growing small business that specializes in providing innovative IT solutions for federal government agencies.  Our expertise lies in accelerating delivery in Data and Analytics, Intelligent Automation, Application Development, and IT Modernization.  We are currently expanding our Federal team and are looking for an Automation Business Analyst. This position is currently remote; however, in accordance with federal contract requirements and company policy, there may be future changes to work location expectations. Candidates should be prepared for the possibility of a return to the office, either partially or fully, based on client directives, contractual obligations, or company policies. Any such changes will be communicated in advance. Qualifications Required - Bachelor's degree, preferably in Computer Science, Information Technology, Computer Engineering, or equivalent education and experience - Experience in RPA business process analysis and documentation preferred - Experience using automation and robotic tools such as UiPath, Blue Prism, or Automation Anywhere preferred - Experience leading a small team of business analysts, providing guidance, mentorship, and oversight to ensure successful project execution. - Ability to conduct workshops with department SMEs to understand the end-to-end process while identifying any automation blockers and the suitability of the process for automation. - Ability to interact with both technical and non-technical stakeholders as part of the RPA delivery cycle. - Prior functional experience in SDLC, Waterfall, and Agile development methodologies including requirements, design, development, testing, documentation, training, deployment, operations, support and maintenance - Need to work closely with internal RPA development team to ensure requirements are accurately mapped and suitable for development - Define the risks, assumptions, and dependencies associated with the process - Visio or similar workflow documentation tool experience - Previous experience working as a business analyst on an Automation/RPA team preferred - Excellent, proactive problem solver, strong analytical skills with the ability to analyze complex requirements and define technical/functional advanced solutions. Preferred Qualifications - UiPath Business Analyst Certification