{"schemaVersion":"jobsearcher.job.v1","id":"cfc5699cb1a0da21c2f9607a","url":"https://jobsearcher.com/jobs/cfc5699cb1a0da21c2f9607a","canonicalUrl":"https://jobsearcher.com/jobs/cfc5699cb1a0da21c2f9607a","title":"Software Engineer","description":"DescriptionHome\r\nSearch Jobs\r\nJob DescriptionSoftware EngineerContract: Westbrook, Maine, USSalary Range: 50.00 - 60.00 | Per HourJob Code: 370565End Date: 2026-08-15\r\nDays Left: 10 days, 3 hours leftApplyPosition DetailsJob Title: Python DeveloperDuration: 6 months100% RemotePay Range: $50/hr - $60/hrWhat you'll work on\r\nAI assistants have made writing code dramatically faster.\r\nThey have not made writing correct code dramatically faster - that gap is widening, and the tooling that closes it matters more than it used to.\r\nThat's the work this role exists to do.\r\nA common thread runs through everything we build: a formal specification - a schema, a contract, a grammar - is the source of truth, and the tooling we write makes other code conform to that specification automatically.\r\nWhen the specification is the source of truth, code that doesn't match it fails loudly rather than silently - whether that code was written by a human, generated by an AI assistant, or somewhere in between.\r\nYour primary focus:Predicate & invariant framework for data contracts - the core of the role.\r\nDesign and implement declarative contract classes that attach to Python methods (design-by-contract decorators - no relation to the Machine Learning data annotations below) and trigger verification of the code inside, using AST-level analysis.\r\nPredicates enforce data contracts: they state what a method must guarantee about the data it produces or consumes, and the verifier checks the implementation against those statements.\r\nInvariants constrain evolution: they state properties of the codebase that must survive change, so that modifications - human- or AI-authored - that would break them fail at verification time, not in production.\r\nYou'll shape the vocabulary of predicates and invariants together with the architect, build the verifier and its diagnostics, and make violation messages clear enough that they teach the contract they enforce.\r\nYour secondary focus:Annotation data platform evolution.\r\nExtend a shipped canonical schema (Avro) and adapter layer that normalize Machine Learning annotation data from multiple commercial labeling platforms into a shared representation.\r\nAdd adapters for new platforms, evolve the schema under a versioned spec and ADR process, and keep validation utilities and Python typing overlays in sync with the schema.\r\nKey responsibilities:Design and implement the predicate/invariant framework: contract classes, the AST-based verifier, and CI integration.\r\nTurn abstract contract concepts into APIs and diagnostics that working engineers adopt willingly - making the ideas graspable is part of the job, not an afterthought.\r\nExtend and evolve schemas, adapters, and validation layers for the annotation platform under its established change process.\r\nInvestigate verification and validation failures and determine whether the fix belongs in the contract, the code, or the source system, documenting your reasoning.\r\nDocument the framework thoroughly and transfer knowledge continuously - by the end of the engagement, the team must be able to own and extend it without you.\r\nWork closely with a senior architect on initial designs, then independently own implementation in your areas.\r\nMust-have qualifications:We're flexible on background, but you should be able to demonstrate: Comfort with formal and abstract structures - logic, type systems, program analysis, algebraic thinking - demonstrated by working software you built from them.\r\nVision and execution together; neither alone is enough.\r\nDeep production Python: decorators, descriptors, metaclasses, type hints, and the standard library.\r\nStrong analytical reasoning: comfort working from ambiguous or underspecified ideas and finding structure.\r\nAbility to communicate technical ideas clearly in writing (design docs, code reviews, documentation, async messaging).\r\nIndependence in scoping and delivering work, with the judgment to escalate complex design questions.\r\nStrong pluses (nice to have, not required):A computer-science degree, or any particular number of years of experience.\r\nPrior data engineering or Machine Learning experience (the role is adjacent to ML, not part of model training).\r\nExperience with our exact stack (Avro, Databricks, Spark, dbt, etc. can be learned on the job).\r\nExperience in any of these areas is a genuine plus:Contracts and verification\r\nDesign-by-contract tooling (icontract, deal, Eiffel, JML, Dafny) or other program-verification exposure.\r\nProperty-based testing (Hypothesis or similar).\r\nCode-as-data work\r\nParsing or analyzing source code (Python ast / libcst, tree-sitter, or equivalents); codemods; mypy plugins or typing internals.\r\nCode generation, templating, or compiler back-ends - especially if you've maintained a code generator in production.\r\nRule and constraint systems.\r\nDSLs, OPA/Rego, rule engines, or knowledge-representation/constraint languages (OWL, RDF, SHACL, Datalog).\r\nTranslating declarative business rules into executable validation logic.\r\nSchema and validation tooling\r\nAvro, JSON Schema, OpenAPI/Swagger, LinkML, CUE, or similar; Pydantic, Marshmallow, or attrs with validators.\r\nThe Company offers the following benefits for this position, subject to applicable eligibility requirements: medical insurance, dental insurance, vision insurance, 401(k) retirement plan, life insurance, long-term disability insurance, short-term disability insurance, paid parking/public transportation, paid time off, paid sick and safe time, hours of paid vacation time, weeks of paid parental leave, and paid holidays annually - as applicable.Job RequirementPython\r\nAST\r\nAvro\r\nMachine Learning\r\nAI\r\nReach Out to a Recruiter\r\nRecruiter\r\nEmail\r\nPhone\r\nSushmita Singh\r\nsushmita.k@collabera.comApply Now","company":"Collabera Technologies","rawCompany":"collabera technologies","city":"Westbrook","state":"ME","isRemote":false,"isActive":false,"createdAt":"2026-08-07T01:40:37.025Z","occupations":[{"code":"15-1252.00","title":"Software Developers","slug":"software-developers"},{"code":"15-1299.08","title":"Computer Systems Engineers/Architects","slug":"computer-systems-engineers-architects"},{"code":"15-1251.00","title":"Computer Programmers","slug":"computer-programmers"}],"industries":[{"code":"541511","title":"Custom Computer Programming Services","slug":"custom-computer-programming-services"},{"code":"513210","title":"Software Publishers","slug":"software-publishers"},{"code":"541512","title":"Computer Systems Design Services","slug":"computer-systems-design-services"}],"jobPosting":{"@context":"https://schema.org","@type":"JobPosting","title":"Software Engineer","description":"DescriptionHome\r\nSearch Jobs\r\nJob DescriptionSoftware EngineerContract: Westbrook, Maine, USSalary Range: 50.00 - 60.00 | Per HourJob Code: 370565End Date: 2026-08-15\r\nDays Left: 10 days, 3 hours leftApplyPosition DetailsJob Title: Python DeveloperDuration: 6 months100% RemotePay Range: $50/hr - $60/hrWhat you'll work on\r\nAI assistants have made writing code dramatically faster.\r\nThey have not made writing correct code dramatically faster - that gap is widening, and the tooling that closes it matters more than it used to.\r\nThat's the work this role exists to do.\r\nA common thread runs through everything we build: a formal specification - a schema, a contract, a grammar - is the source of truth, and the tooling we write makes other code conform to that specification automatically.\r\nWhen the specification is the source of truth, code that doesn't match it fails loudly rather than silently - whether that code was written by a human, generated by an AI assistant, or somewhere in between.\r\nYour primary focus:Predicate & invariant framework for data contracts - the core of the role.\r\nDesign and implement declarative contract classes that attach to Python methods (design-by-contract decorators - no relation to the Machine Learning data annotations below) and trigger verification of the code inside, using AST-level analysis.\r\nPredicates enforce data contracts: they state what a method must guarantee about the data it produces or consumes, and the verifier checks the implementation against those statements.\r\nInvariants constrain evolution: they state properties of the codebase that must survive change, so that modifications - human- or AI-authored - that would break them fail at verification time, not in production.\r\nYou'll shape the vocabulary of predicates and invariants together with the architect, build the verifier and its diagnostics, and make violation messages clear enough that they teach the contract they enforce.\r\nYour secondary focus:Annotation data platform evolution.\r\nExtend a shipped canonical schema (Avro) and adapter layer that normalize Machine Learning annotation data from multiple commercial labeling platforms into a shared representation.\r\nAdd adapters for new platforms, evolve the schema under a versioned spec and ADR process, and keep validation utilities and Python typing overlays in sync with the schema.\r\nKey responsibilities:Design and implement the predicate/invariant framework: contract classes, the AST-based verifier, and CI integration.\r\nTurn abstract contract concepts into APIs and diagnostics that working engineers adopt willingly - making the ideas graspable is part of the job, not an afterthought.\r\nExtend and evolve schemas, adapters, and validation layers for the annotation platform under its established change process.\r\nInvestigate verification and validation failures and determine whether the fix belongs in the contract, the code, or the source system, documenting your reasoning.\r\nDocument the framework thoroughly and transfer knowledge continuously - by the end of the engagement, the team must be able to own and extend it without you.\r\nWork closely with a senior architect on initial designs, then independently own implementation in your areas.\r\nMust-have qualifications:We're flexible on background, but you should be able to demonstrate: Comfort with formal and abstract structures - logic, type systems, program analysis, algebraic thinking - demonstrated by working software you built from them.\r\nVision and execution together; neither alone is enough.\r\nDeep production Python: decorators, descriptors, metaclasses, type hints, and the standard library.\r\nStrong analytical reasoning: comfort working from ambiguous or underspecified ideas and finding structure.\r\nAbility to communicate technical ideas clearly in writing (design docs, code reviews, documentation, async messaging).\r\nIndependence in scoping and delivering work, with the judgment to escalate complex design questions.\r\nStrong pluses (nice to have, not required):A computer-science degree, or any particular number of years of experience.\r\nPrior data engineering or Machine Learning experience (the role is adjacent to ML, not part of model training).\r\nExperience with our exact stack (Avro, Databricks, Spark, dbt, etc. can be learned on the job).\r\nExperience in any of these areas is a genuine plus:Contracts and verification\r\nDesign-by-contract tooling (icontract, deal, Eiffel, JML, Dafny) or other program-verification exposure.\r\nProperty-based testing (Hypothesis or similar).\r\nCode-as-data work\r\nParsing or analyzing source code (Python ast / libcst, tree-sitter, or equivalents); codemods; mypy plugins or typing internals.\r\nCode generation, templating, or compiler back-ends - especially if you've maintained a code generator in production.\r\nRule and constraint systems.\r\nDSLs, OPA/Rego, rule engines, or knowledge-representation/constraint languages (OWL, RDF, SHACL, Datalog).\r\nTranslating declarative business rules into executable validation logic.\r\nSchema and validation tooling\r\nAvro, JSON Schema, OpenAPI/Swagger, LinkML, CUE, or similar; Pydantic, Marshmallow, or attrs with validators.\r\nThe Company offers the following benefits for this position, subject to applicable eligibility requirements: medical insurance, dental insurance, vision insurance, 401(k) retirement plan, life insurance, long-term disability insurance, short-term disability insurance, paid parking/public transportation, paid time off, paid sick and safe time, hours of paid vacation time, weeks of paid parental leave, and paid holidays annually - as applicable.Job RequirementPython\r\nAST\r\nAvro\r\nMachine Learning\r\nAI\r\nReach Out to a Recruiter\r\nRecruiter\r\nEmail\r\nPhone\r\nSushmita Singh\r\nsushmita.k@collabera.comApply Now","datePosted":"2026-08-07T01:40:37.025Z","dateModified":"2026-08-07T01:40:37.025Z","hiringOrganization":{"@type":"Organization","name":"Collabera Technologies","sameAs":"https://jobsearcher.com"},"jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"Westbrook","addressRegion":"ME","addressCountry":"US"}},"identifier":{"@type":"PropertyValue","name":"JobSearcher","value":"cfc5699cb1a0da21c2f9607a"},"url":"https://jobsearcher.com/jobs/cfc5699cb1a0da21c2f9607a"}}