Innodata Inc
Solution Engineer (AI/ML + Software + Data Engineering)
Innodata Inc, Ridgefield Park, New Jersey, us, 07660
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 2,000 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 world’s 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, we’re 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 3,000 employees in the United States, Canada, United Kingdom, the Philippines, India, Sri Lanka, Israel and Germany. We’re 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 Federal’s 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 Innodata’s 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 Innodata’s
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 Innodata’s
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
Bachelor’s degree in Computer Science, Data Engineering, or related STEM discipline (Master’s preferred).
Cloud certifications (AWS, Azure, or GCP) highly desirable.
Required Experience
7–10 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)
Equal Opportunity
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.
#LI-NS1
#J-18808-Ljbffr
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 2,000 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 world’s 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, we’re 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 3,000 employees in the United States, Canada, United Kingdom, the Philippines, India, Sri Lanka, Israel and Germany. We’re 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 Federal’s 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 Innodata’s 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 Innodata’s
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 Innodata’s
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
Bachelor’s degree in Computer Science, Data Engineering, or related STEM discipline (Master’s preferred).
Cloud certifications (AWS, Azure, or GCP) highly desirable.
Required Experience
7–10 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)
Equal Opportunity
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.
#LI-NS1
#J-18808-Ljbffr