Solution Engineer (AIML + Software + Data Engineering)

Position Title: Solution Engineer (AI/ML Software Data Engineering)
Reports To: Vice President Business Development (Innodata Federal)
Job Family: Engineering & Technical Solutions / Proposal Support
FLSA Status: Exempt
Location: Remote (United States) with travel as required
Clearance Requirement: Active TS/SCI required; CI Polygraph preferred

Who we are:

Innodata (NASDAQ: INOD) is a leading data engineering company. With more than 2000 customers and operations in 13 cities around the world we are the AI technology solutions provider-of-choice to 4 out of 5 of the worlds biggest technology companies as well as leading companies across financial services insurance technology law and medicine.

By combining advanced machine learning and artificial intelligence (ML/AI) technologies a global workforce of subject matter experts and a high-security infrastructure were helping usher in the promise of clean and optimized digital data to all industries. Innodata offers a powerful combination of both digital data solutions and easy-to-use high-quality platforms.

Our global workforce includes over 3000 employees in the United States Canada United Kingdom the Philippines India Sri Lanka Israel and Germany. Were poised for a period of explosive growth over the next few years.

About the Role

The Solution Engineer serves as the technical anchor for Innodata Federals Business Development team. This role develops solution architectures authors technical volumes delivers prototypes and provides basis-of-estimate (BOE) inputs for pricing and resourcing. The Solution Engineer ensures Innodatas technical credibility in federal pursuits with applied expertise in AI/ML pipelines data assurance synthetic data and multimodal integration. This position requires mission experience with the Missile Defense Agency (MDA) ephemeris data engineering mobile location data workflows and training dataset quality metrics aligned with Innodatas Assured Data Layer strategy. Priority pursuits include MDA SHIELD DARPA SABER and SDA TAP Lab.

Key Responsibilities

Technical Solution Development (Approx. 35%)

• Develop technical narratives architectures and solution designs for proposals (DoD IC Civilian).

• Author and co-author technical volumes for BAAs CSOs and RFP responses.

• Ensure solutions comply with IL5/IL6 FedRAMP and RMF frameworks.

• Incorporate mission experience supporting MDA SHIELD DARPA SABER and SDA TAP Lab into technical approaches.

Prototype and Demonstration Engineering (Approx. 30%)

• Build and deliver proofs-of-concept (MVPs) aligned with priority pursuits (SHIELD SABER SDA TAP Lab).

• Design and integrate AI/ML workflows with geospatial cyber and mobile data engineering pipelines.

• Develop validate and maintain ephemeris data engineering solutions for space domain awareness and missile defense missions.

• Support technical demonstrations customer briefings and white papers.

Training Dataset Quality & Assurance (Approx. 20%)

• Establish measurable dataset quality metrics (accuracy precision/recall confidence scoring).

• Design and oversee production of gold standard training datasets.

• Build dataset QA/linter pipelines to enforce ontology alignment annotation consistency and quality benchmarks.

• Collaborate with SMEs to ensure dataset assurance aligns with Innodatas Assured Data Layer framework.

Basis of Estimate (BOE) and Cost Support (Approx. 10%)

• Provide labor-hour dataset production and cloud usage estimates.

• Collaborate with BD and finance teams to validate resourcing and cost models.

Customer and Partner Engagement (Approx. 5%)

• Represent Innodata in technical discussions with government customers and prime partners.

• Translate mission requirements into feasible architectures and executable MVPs.

• Support teaming strategies by aligning technical discriminators to win themes.

Technical Expertise

• 8 years of software engineering experience with 3 years in engineering leadership roles

• Strong proficiency in modern programming languages (Python JavaScript/TypeScript Go or similar)

• Experience building and scaling platform products APIs and developer tools

• Deep understanding of AI/ML systems model training pipelines and evaluation frameworks

• Knowledge of cloud infrastructure containerization and microservices architecture

• Experience with databases data pipelines and distributed systems

Leadership & Management

• Proven track record of building and leading high-performing engineering teams

• Experience mentoring engineers and fostering technical growth

• Strong project management skills with ability to deliver complex initiatives on time

• History of establishing engineering processes and development methodologies

Collaboration & Communication

• Excellent communication skills with ability to explain technical concepts to diverse audiences

• Experience working closely with Data Science Product and cross-functional teams

• Strong stakeholder management and expectation-setting abilities

• Collaborative leadership style with focus on team empowerment

Business Acumen

• Understanding of platform business models and customer needs

• Experience with both internal tooling and external customer-facing products

• Knowledge of enterprise software requirements including security compliance and scalability

Preferred Qualifications

• Experience in AI/ML companies or data annotation/labeling platforms

• Background with model evaluation monitoring and MLOps workflows

• Knowledge of annotation standards and data quality management

• Experience building developer-facing APIs and SDKs

• Previous experience in a player-coach role balancing coding and management

• Familiarity with agentic AI systems and evaluation methodologies

Required Education & Certifications

• Bachelors degree in Computer Science Data Engineering or related STEM discipline (Masters preferred).

• Cloud certifications (AWS Azure or GCP) highly desirable.

Required Experience

• 710 years in software or data engineering; 5 years in AI/ML pipeline design and implementation.

• Demonstrated experience with Missile Defense Agency (MDA) systems and mission data.

• Hands-on expertise in ephemeris data engineering and mobile location data workflows.

• Proven success designing dataset QA metrics and delivering gold standard datasets.

• Familiarity with synthetic data workflows and model assurance techniques (bias detection adversarial testing).

• Knowledge of DoD/IC compliance frameworks (FedRAMP RMF IL5/IL6).

• Strong record of technical proposal authorship and capture support.

Knowledge Skills and Abilities (KSAs)

Knowledge:

• AI/ML pipelines multimodal data fusion ephemeris data and mobile location data.

• Ontology/taxonomy engineering and dataset normalization.

• Dataset assurance frameworks (confidence scoring precision/recall provenance tracking).

• Federal proposal lifecycle and Shipley capture methodology.

Skills:

• Technical writing for proposals and white papers.

• Solution architecture and prototype development.

• Data pipeline engineering and cloud-native deployment.

• Dataset QA/QC pipeline development.

Abilities:

• Communicate complex technical concepts to technical and executive audiences.

• Manage multiple proposals and prototypes under tight deadlines.

• Deliver mission-ready solutions that directly support capture wins.

Work Environment & Physical Requirements

• Work performed in remote office environments Innodata facilities and secure government locations (SCIFs).

• Must be able to sit at a computer for extended periods communicate verbally and in writing and occasionally lift up to 25 lbs. for proposal materials.

• Must be able to obtain and maintain a TS/SCI security clearance with polygraph.

Travel Requirements

• Up to 25% domestic travel for customer engagement partner meetings and technical demonstrations.

Career Development

• Continuing professional development in AI/ML dataset assurance space data engineering and federal acquisition.

• Growth pathway includes Chief Solutions Engineer Capture Technical Lead or Program Manager roles.

Labor Category Mapping (for Proposals)

• Labor Category Title: Solution Engineer (AI/ML Software Data Engineering)

• Mapping Equivalent: Senior Solutions Engineer / SME IV (GS-14/15 equivalent)

• Clearance: TS/SCI with CI Poly (or eligible)

We are an equal opportunity employer committed to fostering an inclusive respectful and diverse workplace. We welcome and encourage applications from individuals of all backgrounds and are dedicated to employment equity and building a team that reflects the diverse communities in which we live and operate.

Please be aware of recruitment scams involving individuals or organizations falsely claiming to represent employers. Innodata will never ask for payment banking details or sensitive personal information during the application process. To learn more on how to recognize job scams please visit the Federal Trade Commissions guide at you believe youve been targeted by a recruitment scam please report it to Innodata at and consider reporting it to the FTC at .

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